เงื่อนไขการค้นหา

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Big Data, Cloud Computing

ประเภทงาน:

งานประจำ

• Shanghai, China.
• Workplace: on_site.
• Department: Technology.
• We are seeking an experienced Senior Data Engineer to design, implement, and maintain our data infrastructure and pipelines. The ideal candidate will have a strong background in data engineering, big data technologies, and cloud platforms. You will work closely with data scientists, analysts, and other stakeholders to ensure efficient and reliable data processing and storage solutions and who has mind set things to done.
• Design, develop, and maintain scalable data pipelines and ETL processes.
• Implement and optimize data storage solutions, including data warehouses and data lakes.
• Collaborate with data scientists and analysts to understand data requirements and provide efficient data access.
• Ensure data quality, consistency, and reliability across all data systems.
• Develop and maintain data models and schemas.
• Implement data security and access control measures.
• Optimize query performance and data retrieval processes.
• Evaluate and integrate new data technologies and tools.
• Mentor junior data engineers and provide technical leadership.
• Collaborate with cross-functional teams to support data-driven decision-making.
• Bachelor's or master's degree in computer science, Engineering, or a related field.
• 5+ years of experience in data engineering or related roles.
• Strong programming skills in Python, Java, or Scala.
• Extensive experience with big data technologies such as Hadoop, Spark, and Hive.
• Proficiency in SQL and experience with both relational and NoSQL databases.
• Experience with cloud platforms (AWS, Azure,) and their data services.
• Knowledge of data modeling, data warehousing, and ETL best practices.
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills as well.
• Preferred.
• Experience with stream processing technologies (eg Kafka, Flink or delta live table ).
• Familiarity with data governance and compliance requirements.
• Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).
• Contributions to open-source projects or relevant certifications.
• Experience in Tencent big data platform.
• Experience in PowerBI will be preferable.
• Apply.
• Apply at CP Axtra](https://apply.workable.com/joinmakropro/j/02AC2EB4BB/apply).

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Industry trends, Teamwork, Big Data, Kafka, Cloud Computing

ประเภทงาน:

งานประจำ

• Design, build, and maintain data pipelines and infrastructure to support data-driven initiatives.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver scalable solutions.
• Develop and maintain data models, data dictionaries, and data transformation processes.
• Monitor and troubleshoot data pipelines to ensure data quality and availability.
• Implement and maintain data security and privacy measures.
• Continuously evaluate and improve data systems to optimize performance and scalability.
• Keep up-to-date with industry trends and best practices in data engineering and apply them to our data systems.
• Mentor and train junior data engineers on data engineering best practices and technologies.
• Bachelor's degree in Computer Science, Information Systems, or a related field.
• Minimum of 3 years of experience in data engineering.
• Strong experience with Databricks and other big data technologies such as PySpark, and Kafka.
• Proficient in SQL and experience with data modeling and ETL processes.
• Experience with cloud platforms such as AWS or Azure.
• Knowledge of data security and privacy principles.
• Strong problem-solving and analytical skills.
• Excellent communication and teamwork abilities.
• Proven ability to work in a fast-paced and dynamic environment.
• Why Join Us?.
• Opportunity to work with cutting-edge technologies and innovative solutions.
• Dynamic and collaborative work environment.
• Competitive salary and benefits package.
• Career growth and development opportunities.
• Work-life balance and flexible working hours.
• Fun and inclusive company culture.
• If you are passionate about data engineering and want to be a part of a dynamic team that is driving innovation in Thailand, then we want to hear from you. Apply now to join Gosoft(Thailand)Co.,Ltd. as a Data Engineer and take your career to the next level.

ทักษะ:

Data Analysis, Architecture, Labor law, Teamwork, Big Data

ประเภทงาน:

งานประจำ

• Build and maintain data pipelines to collect, transform, and store data from robotic systems and sensors.
• Design data architecture to support real-time and historical data analysis.
• Implement ETL processes and ensure data quality, validation, and monitoring.
• Optimize database performance and manage large-scale data storage (structured and unstructured).
• Collaborate with AI, robotics, and software teams to align data workflows with operational needs.
• Maintain data documentation and ensure compliance with data privacy and security standards.
• Demonstrate a commitment to improve and comply with SSHE policy, environment regulations as well as labor law.
• Perform other related duties as assigned.
• Skills and Abilities.
• Excellent analytical and problem-solving skills.
• Understanding about metadata and data governance.
• Familiar with a variety of software patterns and principles.
• Understanding of big data architecture and streaming analytics.
• Has a good understanding of software engineering principles.
• Experience designing software applications running on multiple platform types.
• Experience in evaluating machine learning applications.
• Ability to effectively communicate product architectures, design proposals and negotiate options at management levels.
• Competencies.
• I DREAM - Passion.
• I DREAM - Fun.
• I DARE - Innovate.
• I DARE - Drive Result.
• WE DO - Respect.
• WE DO - Teamwork.

ทักษะ:

Python, Cloud Computing, SQL

ประเภทงาน:

งานประจำ

• Design, build, and maintain scalable data solutions that support reporting, self-service analytics, and advanced analytics.
• Work primarily on the organization's data platform, currently centered on Snowflake and IICS, to transform raw data into trusted, business-ready data assets.
• Partner closely with Data Analysts and source-system teams to translate business needs into data models, pipelines, and reusable data products.
• Use AI-assisted development practices across the full delivery lifecycle to improve design quality, development efficiency, testing, documentation, and technical communication.
• Apply modern data engineering practices while maintaining strong fundamentals in data modeling, ETL/ELT, orchestration, and data quality.
• Design, develop, and maintain data pipelines, transformations, and orchestration workflows that ingest, curate, and publish data for analytics use cases.
• Build and enhance data models based on business analysis and reporting requirements.
• Work with structured and semi-structured data from enterprise systems and files, including relational databases, JSON, and XML.
• Collaborate with Data Analysts, source-system developers, and business stakeholders to define requirements and deliver fit-for-purpose data solutions.
• Improve engineering productivity by using AI tools for code support, testing framework creation, documentation, diagramming, and solution exploration.
• Support data quality, performance optimization, maintainability, and operational reliability of data solutions.
• Enable business reporting, self-service analytics, and foundational data assets for advanced analytics and data science teams.
• Follow established organizational standards for governance, security, access control, and data handling.

ทักษะ:

Cloud Computing, Amazon AWS

ประเภทงาน:

งานประจำ

Designing and implementing data pipelines that extract data from various sources, transform it into a suitable format, and load it into data storage systems. - Integrating data from multiple sources, which can include databases, APIs, logs, and external data sets, to create a unified view of data. - Setting up and managing data warehouses or data lakes where large voulumes of data can be stored and easily accessed for analytical purposes. - Implementing data governance practices to ensure data is managed in a consistent and standardized way across the organization. - Implementing d ...

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Architecture, Big Data, DevOps, Python, English

ประเภทงาน:

งานประจำ

• A successful candidate will be working with our cloud-based Big Data Platform to digest marketplace data either structured or unstructured from different marketplaces in order to facilitate data utilization. The candidate will have to design and implement a strategic way to utilize all the data extracted from several marketplaces.
• The candidate will be also working closely with other application teams and product managers in order to align with other teams and business roadmap.
• Participate in designing and implementing as well as maintaining data pipelines for ...
• Demonstrate continuous improvement by inspecting and adopting new ideas for improving solutions, tools and processes.
• Work closely with members of IT (e.g. Architecture, DevOps and Business Analysts) to ensure the highest quality softwareCoach fellow associate data engineers.
• Capabilities.
• Bachelor Degree from Computer Engineering, Computer Science or related fields.
• Good knowledge of SQL, relational database design and efficient methods for working with large size of data.
• Good knowledge of Python.
• Understanding of fundamental design principles behind data-oriented application.
• Ability to understand business requirements and be able to express them in computer language.
• Ability to communicate in English, both written and oral form.

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Microsoft Azure, Python, Apache, Kafka, SQL

ประเภทงาน:

งานประจำ

• You have hands-on experience delivering end-to-end data solutions and a strong foundation in areas such as large-scale data processing, data infrastructure engineering, or data modeling.
• You are proficient in Python and SQL, and apply solid engineering practices including testing, version control, CI/CD, and writing maintainable code.
• You have strong, practical experience with Databricks and Apache Spark, and are capable of building, optimizing, and operating production-grade data pipelines.
• You have experience working with streaming data or event-driven pipelines using Kafka or similar technologies.
• You are familiar with workflow orchestration using tools like Airflow, Azure Data Factory, or similar platforms for scheduling, monitoring, and managing data pipelines.
• You have experience working with cloud-based data platforms, particularly on Microsoft Azure; exposure to AWS is a plus.
• You collaborate effectively across teams, communicate clearly, and use strong data intuition to design valuable analytical or operational solutions.
• You are curious, resilient, and thoughtful - comfortable learning new technologies, embracing feedback, and improving how things are done.

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Google Cloud Platform, Google Analytics, TensorFlow, Big Data, Tableau, Python, Hadoop, Kafka, Scala, Java, SQL, English

ประเภทงาน:

งานประจำ

• Develop big data solutions for batch processing and near real-time streaming.
• Retrieve, prepare, and process a rich data variety of data sources.
• Work with business domain experts, data scientists and application developers to identify data that is relevant for analysis.
• Keep abreast of new developments in the big data ecosystem and learn new technologies.
• Triage code problems and data-related issues.
• 3+ years of experience with relational database systems, with expertise in SQL.
• 3+ years of programming experience in Java, Python, Scala or similar.
• 3+ years of experience in coding in data management, data warehousing or unstructured data environments.
• Experience with cloud-based platforms such as AWS, Google Cloud platform or similar.
• Experience building complex pipelines using automated workflow is a plus, e.g. Luigi, Airflow, Oozie or similar.
• Experience with parallel data processing is a plus, e.g. MapReduce, Hadoop, Spark or similar.
• Experience with streaming technologies is a plus, e.g. Kafka, AWS Kinesis or similar.
• Experience with Business Intelligence tools and platforms is a plus, e.g. Tableau, QlikView, PowerBI, Google Analytics or similar.
• Experience with Machine Learning is a plus, e.g. TensorFlow, NumPy, Scikit-Learn, Mahout or similar.
• Good communication in English.

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Problem Solving, Enthusiastic, Teamwork, SQL, English

ประเภทงาน:

งานประจำ

• We're committed to bringing passion and customer focus to the business.*.
• If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!*.
• Lumentum is seeking a.
• Senior Data Engineer.
• to join our Data Science and Data Engineering team. In this role, you will design, build, and optimize scalable data platforms, pipelines, and analytics solutions that enable data-driven decision-making across the enterprise. You will work closely with business leaders, data scientists, analysts, and technology teams to transform complex data into actionable insights that drive operational excellence, business growth, and strategic outcomes.
• This is an opportunity to play a.
• key role.
• in advancing Lumentum's enterprise analytics capabilities by developing modern data architectures, improving data quality and accessibility, and enabling AI and advanced analytics initiatives. You will collaborate across functions including Sales, Operations, Manufacturing, Supply Chain, and Finance to deliver impactful solutions in a fast-paced and innovative environment.
• Design, develop, and maintain scalable data pipelines, data products, and enterprise data models that support analytics, reporting, machine learning, and AI initiatives across Lumentum.
• Build and optimize modern data architectures using Databricks, Delta Lake, Spark, SQL, and cloud-native technologies to enable high-performance analytics and trusted business insights.
• Develop and maintain curated semantic layers, business metrics, and governed datasets that power self-service analytics and conversational AI solutions such as Databricks Genie and other natural language query platforms.
• Partner with business stakeholders across Sales, Operations, Manufacturing, Supply Chain, Finance, and HR to translate business requirements into scalable data solutions and reusable data assets.
• Enable business users to interact with enterprise data through natural language interfaces by designing data models, metadata frameworks, business glossaries, and governance standards that improve AI-generated insights and query accuracy.
• Collaborate with Data Scientists, Analytics Engineers, and BI developers to support advanced analytics, predictive modeling, and AI-driven decision-making.
• Establish data quality, lineage, observability, and governance frameworks to ensure trusted, secure, and compliant enterprise data assets.
• Design and implement enterprise-wide KPI frameworks and metric definitions to create a single source of truth across functional domains.
• Optimize data performance, reliability, and scalability while reducing technical debt and improving platform efficiency.
• Support the development of AI-enabled analytics capabilities, including retrieval-augmented generation (RAG), vector search, knowledge repositories, and semantic search solutions that enhance data discovery and business productivity.
• Drive adoption of modern data engineering best practices including CI/CD, Infrastructure as Code, automated testing, and data lifecycle management.
• Partner with leadership and analytics teams to advance Lumentum's vision of a centralized, AI-enabled analytics organization.
• Degree in Computer Engineering, Computer Science, IT, or related fields.
• 10+years of hands-on experience as a Data Engineer or similar role.
• Strong SQL and data modeling skills, including Databricks, Delta Lake, Spark, SQL, and cloud-native technologies.
• Strong analytical, troubleshooting, and problem-solving skills with the ability to support production environments.
• Good communication, problem solving skills, and teamwork mindset.
• Excellent English proficiency (reporting to foreign national).
• We are an equal opportunity employer and value diversity at our company. *.
• We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. *.
• We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. *.
• Please contact us to request accommodation.*.

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Analytical Thinking, Problem Solving, Architecture, Accounting, Power BI, YouTube, Python, Java, SQL, English, Thai

ประเภทงาน:

งานประจำ

• Eligibility and details may vary according to work location, service year and conditions in each program/plan.
• Please note benefits may be changed from time to time without notice, subject to the direction and discretion of the Company and/or applicable law.
• Application Process.
• Please be informed that only shortlisted candidates will be notified, and you can find out more about our hiring process.
• here.
• For more information about business solicitation and recruiting scams, please click.
• here.
• We thank you for your interest in ExxonMobil.".
• Stay connected with us.
• Learn more at our.
• website.
• Follow us on.
• LinkedIn.
• and.
• X.
• Like us on.
• Facebook.
• Subscribe our channel at.
• YouTube.
• Equal Opportunity Employer.
• ExxonMobil is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity, national origin, citizenship status, protected veteran status, genetic information, or physical or mental disability.
• Corporate Separateness Statement.
• Nothing herein is intended to override the corporate separateness of local entities. Working relationships discussed herein do not necessarily represent a reporting connection, but may reflect a functional guidance, stewardship, or service relationship.
• Exxon Mobil Corporation has numerous affiliates, many with names that include ExxonMobil, Exxon, Esso and Mobil. For convenience and simplicity, those terms and terms like corporation, company, our, we and its are sometimes used as abbreviated references to specific affiliates or affiliate groups. Abbreviated references describing global or regional operational organizations and global or regional business lines are also sometimes used for convenience and simplicity. Similarly, ExxonMobil has business relationships with thousands of customers, suppliers, governments, and others. For convenience and simplicity, words like venture, joint venture, partnership, co-venturer, and partner are used to indicate business relationships involving common activities and interests, and those words may not indicate precise legal relationships.
• Functional Skills.
• Applied Software Engineering for Data.
• Data Architecture & Strategy.
• Data Integration.
• Data Management.
• Data Visualization.
• Data Modeling.
• Machine Learning.
• Nothing herein is intended to override the corporate separateness of local entities. Working relationships discussed herein do not necessarily represent a reporting connection, but may reflect a functional guidance, stewardship, or service relationship.
• Exxon Mobil Corporation has numerous affiliates, many with names that include ExxonMobil, Exxon, Esso and Mobil. For convenience and simplicity, those terms and terms like corporation, company, our, we and its are sometimes used as abbreviated references to specific affiliates or affiliate groups. Abbreviated references describing global or regional operational organizations and global or regional business lines are also sometimes used for convenience and simplicity. Similarly, ExxonMobil has business relationships with thousands of customers, suppliers, governments, and others. For convenience and simplicity, words like venture, joint venture, partnership, co-venturer, and partner are used to indicate business relationships involving common activities and interests, and those words may not indicate precise legal relationships.

ทักษะ:

Big Data, Hadoop, Python, Kafka, Scala

ประเภทงาน:

งานประจำ

• Work closely with the team of engineers, strategists and data scientists to build customer-facing products to address business problems.
• Build state-of-the-art data infrastructure to unlock full potential of ABACUS digital' data analytics capabilities. This includes, but not limited to, data integration (from both internal and external sources), large-scale data pipelines, data workflow management, and ML/AI real-time inference service.
• Implement an experimentation platform that enables the team to conduct online experi ...
• looking for.
• BS/MS degree in Computer Engineering, Computer Science, or a related field.
• Fresh grads are welcome! But having a full-time experience in tech or related industry is a plus.
• Proficiency with at least one of these programming languages: Java, Scala, Python, any other OOP languages, or other functional languages.
• Interested in building and troubleshooting large-scale distributed products.
• Interested in big data technologies such as Hadoop, Hive, Avro, Parquet, Presto, Spark, or Kafka is highly desired.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Cloud Computing

ประเภทงาน:

งานประจำ

• Design, develop, and maintain scalable ETL / ELT pipelines.
• Build and optimize data workflows on Databricks and Azure Cloud.
• Develop high-performance SQL transformations and data models.
• Work with large-scale structured and semi-structured datasets.
• Improve data quality, reliability, and pipeline performance.
• Support migration and modernization of enterprise data platforms.
• Collaborate with stakeholders to understand business and technical requirements.
• Troubleshoot production issues and optimize existing data processes.
• Participate in architecture and technical solution discussions.
• Mentor junior engineers and share best practices with the team.
• At least 5 years of experience in Data Engineering or related roles.
• Strong expertise in SQL and ETL development.
• Hands-on experience with Azure Cloud and Databricks.
• Experience working with enterprise-scale data platforms.
• Strong understanding of Data Warehouse and Data Lake concepts.
• Experience with PySpark / Spark is highly preferred.
• Familiarity with cloud-based data architecture and optimization.
• Experience in performance tuning and troubleshooting ETL jobs.
• Understanding of CI/CD and version control (Git).
• Good problem-solving and analytical skills.
• Able to work independently and communicate effectively with teams.

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Big Data, Cloud Computing, Amazon AWS

ประเภทงาน:

งานประจำ

• Phra Khanong, Bangkok.
• Reports to Head of Enterprise Data Solutions.
• Help Build the Future of Insurance Data in Thailand!!!.
• Are you a problem solver who loves working with data? Do you enjoy fixing messy systems, improving performance, and building new data platforms from the ground up?.
• We're looking for a Data Engineer who's ready to roll up their sleeves and tackle real-world challenges - from messy pipelines and performance bottlenecks to cloud modernization and data governance.
• Design, develop, and maintain robust data pipelines using Apache Airflow, SSIS, PySpark, and Talend to ingest, transform, and load large-scale datasets (300M+ rows) from multiple sources.
• Manage and optimize relational databases including Oracle and SQL Server, ensuring high performance and scalability for analytical workloads.
• Design, build, and maintain cloud data platforms and warehousing solutions using AWS services such as Redshift and S3, alongside ClickHouse for high-performance analytical querying.
• Develop and maintain OLAP solutions using SSAS for advanced reporting and analytics, including cube design, partitioning, and aggregation strategies.
• Implement ETL processes for structured and semi-structured data, ensuring data quality, consistency, and compliance with industry standards.
• Collaborate with the BI Team, Actuarial Team, and business stakeholders to understand requirements and deliver efficient data models and solutions.
• Monitor and improve data pipeline performance, troubleshoot bottlenecks, and implement best practices for parallel processing and resource optimization.
• Ensure data security and compliance with insurance industry regulations and company policies.
• Leverage big data technologies such as Apache Spark for distributed processing and advanced data transformations.
• Automate workflows and scheduling using Airflow DAGs, ensuring reliability and scalability of data operations.
• Document data architecture, processes, and standards, and provide technical guidance to team members.
• Required.
• Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related field.
• 3-5 years of experience building and maintaining data pipelines.
• Proficiency in SQL and experience with relational databases (Oracle, SQL Server), including performance tuning and query optimization.
• Hands-on experience with ETL tools such as SSIS, Talend, and PySpark, and data modeling for OLAP solutions using SSAS.
• Knowledge of data pipeline orchestration using Apache Airflow.
• Experience with big data processing frameworks such as Apache Spark for distributed data transformations.
• Hands-on experience with cloud database/data platform services such as AWS Redshift, S3, and ClickHouse.
• Solid understanding of data warehousing concepts, star/snowflake schema, and partitioning strategies for large datasets (300M+ rows).
• Proficiency in Python or another scripting language for automation and data manipulation.
• Knowledge of data quality, governance, and security best practices.
• Ability to work with large-scale data and optimize workflows for performance and scalability.
• Familiarity with insurance industry data or other regulated environments is a plus.
• Preferred.
• Experience with Power BI and building efficient data marts.
• Experience with data privacy, governance, and secure data access practices.
• Hands-on with additional cloud platforms/tools such as Azure, Databricks, Delta Lake, Snowflake, or the Hadoop ecosystem.
• Able to troubleshoot performance issues in both backend pipelines and frontend analytics tools.
• Comfortable working in a fast-paced, high-ownership environment with cross-functional teams.
• Why Join Us.
• Build Thailand's insurance data infrastructure from the ground up - real ownership over pipelines and platforms that power an entire industry, not just one company.
• Work with a modern, varied tech stack (Airflow, Spark, AWS, ClickHouse) and real scale (300M+ row datasets), with room to modernize legacy systems your way.
• Close collaboration with BI and Actuarial teams gives you direct visibility into how your data work drives business and industry decisions.

ทักษะ:

Big Data, SQL

ประเภทงาน:

งานประจำ

• Work Independently or in team to provide big data infrastructure to solve big data requirement in mid-to-large organization.
• Develop end-to-end data analytics processes including, integrate, transform, analyze and visualization. By using our big data software.
• Handle structured (SQL), ensuring proper storage and retrieval of Big data.
• Work closely with Data Analysts, and Software Engineers to ensure smooth data operations and provide the necessary infrastructure for data-driven decision-making.
• Growth with Tech leader company. Apply here!.

ทักษะ:

Architecture, Automation, Big Data, Python, Docker, Kafka, SQL, ETL

ประเภทงาน:

งานประจำ

• Data Pipeline & Architecture.
• ออกแบบและสร้างท่อส่งข้อมูล (ETL/ELT Pipelines) ทั้งแบบ Batch และ Real-time.
• เชื่อมต่อข้อมูลจากแหล่งต่าง ๆ เช่น Database, REST APIs, และ Message Queues.
• ออกแบบและวางรากฐานโครงสร้างข้อมูล (Data Schema) เพื่อรองรับการทำ Data Analytics เชิงลึก พร้อมทั้งวางแผนและบริหารจัดการการพัฒนาเครื่องมือภายใน (Internal Tools).
• ตรวจสอบและแก้ไขปัญหา Query ที่ทำงานช้า (Slow Query).
• ออกแบบ Index และโครงสร้างข้อมูลเพื่อเพิ่มประสิทธิภาพการดึงข้อมูล.
• Data Quality & Monitoring.
• ตรวจสอบความถูกต้อง (Data Validation) และความสะอาดของข้อมูลก่อนนำเข้าสู่ระบบ.
• สร้างระบบ Monitoring และ Alerting เมื่อระบบ Pipeline เกิดข้อผิดพลาด รวมถึงพบความผิดปกติของ Data.
• DataOps & Automation.
• ใช้ GitLab CI/CD ในการทำ Automated Testing และ Deploy ระบบ Pipeline.
• จัดการ Containerization ด้วย Docker เพื่อให้ระบบทำงานได้เสถียรในทุก Environment.
• Collaboration & Documentation.
• ทำงานร่วมกับ Data Analyst และทีม Developer เพื่อเปลี่ยนความต้องการทางธุรกิจให้เป็น Technical Solution.
• จัดทำเอกสาร Data Dictionary และ Data Lineage เพื่อความโปร่งใสของที่มาข้อมูล.
• ทักษะทางเทคนิค (Technical Skills).
• Languages: Advanced SQL (Window Functions, CTEs), และ Python (Pandas, PySpark).
• Concepts: เข้าใจหลักการ Data Warehouse, Data Lake, และ Big Data สถาปัตยกรรมต่าง ๆ.
• Cloud: มีประสบการณ์ใช้งาน Cloud Data Warehouse และ Cloud Storage (AWS, Azure, หรือ GCP).
• Version Control: ใช้งาน Git (GitLab, GitHub) ได้คล่องแคล่ว (Branching, Merge Request).
• Data Structures & Algorithms: เข้าใจพื้นฐานในระดับที่สามารถออกแบบโค้ดที่มีประสิทธิภาพ.
• ทักษะเพิ่มเติม (จะพิจารณาเป็นพิเศษ).
• Streaming: มีความเข้าใจระบบ Message Broker เช่น Kafka หรือ RabbitMQ.
• Orchestration: เคยใช้งานเครื่องมือจัดการลำดับงาน เช่น Airflow หรือ Prefect.
• Tools: มีประสบการณ์การใช้ dbt (Data Build Tool) ในการจัดการ SQL Models.
• ผู้ถือสัญชาติไทยเท่านั้น.
• วุฒิการศึกษาระดับปริญญาตรีในสาขา Computer Engineering, IT หรือสาขาที่เกี่ยวข้อง.
• ประสบการณ์ 1-3 ปี (หากเป็นเด็กจบใหม่ ต้องมี Portfolio หรือโปรเจกต์ที่เกี่ยวข้องอย่างชัดเจน).
• มีทักษะการคิดเชิงตรรกะ (Logical Thinking) และความสามารถในการสื่อสารเรื่องเทคนิคให้คนทั่วไปเข้าใจได้ง่าย.
• มีทักษะด้านการสื่อสารและการประสานงานที่มีประสิทธิภาพ.
• มี Growth Mindset.
• สมัครงาน.
• หรือแนะนำผู้อื่น.
• แชร์.
• Facebook.
• Line.
• LinkedIn.
• X (Formerly Twitter).
• Whatsapp.
• Email.

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Analytical Thinking, Data Warehousing, Microsoft Azure, Architecture, Automation

ประเภทงาน:

งานประจำ

• Design, develop, implement, and maintain enterprise data integration solutions, data pipelines, and data platform services.
• Manage and support Microsoft Azure data platform components, including Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, and related services.
• Support the adoption, implementation, and continuous improvement of Microsoft Fabric technologies and modern data platform architectures.
• Develop and maintain ETL / ELT processes to ensure reliable movement and availability of business data across enterprise systems.
• Monitor platform performance, availability, capacity, and operational health to ensure service reliability.
• Data Quality and Reliability.
• Establish and maintain data quality controls, validation processes, and reconciliation procedures.
• Investigate, troubleshoot, and resolve data platform incidents, data inconsistencies, and integration failures.
• Monitor and improve data timeliness, accuracy, completeness, and reliability.
• Support business users in identifying, analyzing, and resolving data-related issues.
• Data Governance and Security.
• Maintain data lineage, metadata, data catalogues, and technical documentation for enterprise data assets.
• Support implementation of data governance standards, policies, and best practices.
• Ensure compliance with information security, privacy, and regulatory requirements, including PDPA.
• Implement and maintain appropriate data protection controls, including encryption, access management, data masking, and row-level security.
• Participate in audit, compliance, risk assessment, and remediation activities related to the data platform.
• Business and Vendor Collaboration.
• Collaborate with business units to gather requirements and translate business needs into scalable data solutions.
• Support reporting, analytics, automation, and business intelligence initiatives across the organization.
• Coordinate with external vendors, consultants, and system owners during integrations, upgrades, and project implementations.
• Provide technical guidance and recommendations on data architecture, platform enhancements, and emerging technologies.
• Documentation and Continuous Improvement.
• Develop and maintain technical documentation, architecture diagrams, operational procedures, and support materials.
• Maintain version-controlled repositories and ensure proper documentation of platform configurations and changes.
• Identify opportunities to improve platform performance, scalability, security, reliability, and cost efficiency.
• Continuously develop knowledge and skills related to Microsoft data platform technologies and industry best practices.
• Perform other.
• as assigned by management.
• Bachelor's degree or higher in Computer Science, Information Technology, Data Engineering, Computer Engineering, Statistics, or a related field.
• Minimum 2 years of experience in Data Engineering, Data Warehousing, Analytics Engineering, Business Intelligence, or a related technology discipline.
• Experience designing, implementing, and supporting enterprise data platforms and data integration solutions.
• Strong proficiency in SQL and relational database technologies, including data modelling and data warehouse concepts.
• Hands-on experience with Microsoft Azure data services, including Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake Storage.
• Experience developing and maintaining ETL / ELT pipelines for operational reporting, analytics, and business intelligence solutions.
• Understanding of data governance, data lineage, metadata management, and data quality management practices.
• Knowledge of data security principles, including access control, encryption, data masking, and privacy regulations such as PDPA.
• Experience working with Git or other version control platforms for development and configuration management.
• Experience working with business stakeholders to gather requirements and translate them into technical solutions.
• Ability to investigate and resolve complex data platform issues, data quality concerns, and integration failures.
• Strong communication, documentation, analytical thinking, and stakeholder management skills.
• Experience coordinating with external vendors, system integrators, and technology partners is preferred.
• Experience with Microsoft Fabric, Microsoft Purview, hospitality systems, or multi-site operations environments is an advantage.
• Possesses a service-oriented mindset, demonstrates initiative, and continuously seeks opportunities to improve platform reliability, performance, security, and data quality.

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Data Warehousing, Automation, Apache, Python, ETL

ประเภทงาน:

งานประจำ

• Data Pipeline Operations.
• Monitor scheduled and event-driven ETL/ELT pipelines across Azure Data Factory, Databricks, Airflow, and related platforms.
• Investigate failed jobs, delayed data, missing records, schema changes, and dependency issues.
• Rerun or recover pipelines using approved operational procedures and confirm successful completion.
• Support production releases, cutovers, and post-deployment monitoring.
• Incident and Problem Management.
• Respond to data-service incidents and operational requests within agreed service levels.
• Perform root-cause analysis and document the issue, impact, resolution, and preventive action.
• Create, update, and follow operational tickets through closure.
• Coordinate with source-system owners, data engineers, infrastructure teams, and report owners when cross-team support is required.
• Data Quality and Reliability.
• Validate data completeness, accuracy, freshness, and reconciliation results.
• Maintain monitoring, alerting, and operational checks for critical pipelines and datasets.
• Identify recurring failure patterns and recommend permanent fixes or automation.
• Escalate material data risks with clear impact and status communication.
• Stakeholder and Service Support.
• Support users of reports, dashboards, and downstream data products.
• Provide concise updates on incidents, blockers, ownership, and expected next actions.
• Participate in daily operational reviews and handovers.
• Maintain runbooks, troubleshooting guides, support knowledge, and service documentation.
• Continuous Improvement.
• Automate repetitive operational tasks and recovery steps where appropriate.
• Contribute to observability, cost, performance, and reliability improvements.
• Support standardization of deployment, support, and data-quality practices.
• Share lessons learned and help improve team operational readiness.
• Required.
• Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related discipline, or equivalent practical experience.
• 2-5 years of experience in data engineering, data operations, application support, or production support.
• Hands-on experience supporting production data pipelines or data platforms.
• Strong SQL skills and working knowledge of Python or another scripting language.
• Experience with one or more orchestration or processing technologies such as Azure Data Factory, Databricks, Apache Spark, or Airflow.
• Understanding of data warehousing, ETL/ELT, file and database integration, job dependencies, and data-quality controls.
• Ability to troubleshoot methodically, communicate clearly, and work across technical and business teams.
• Preferred.
• Experience with Azure or AWS data services.
• Experience with Linux, shell scripting, Git, and CI/CD practices.
• Familiarity with monitoring platforms such as Azure Monitor, CloudWatch, Grafana, or equivalent tools.
• Experience with Jira or an IT service-management platform.
• Retail, e-commerce, finance, supply-chain, or enterprise analytics experience.
• Knowledge of access controls, secrets management, and secure production-support practices.
• Production ownership and service mindset.
• Structured troubleshooting and root-cause analysis.
• Attention to data quality and operational detail.
• Clear incident communication and stakeholder coordination.
• Prioritization under pressure.
• Continuous improvement and automation mindset.

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Problem Solving, Leadership Skill, Teamwork, Cloud Computing, English

ประเภทงาน:

งานประจำ

• Design, develop, and maintain scalable data pipelines, data products, and enterprise data.
• models that support analytics, reporting, machine learning, and AI initiatives across.
• Lumentum.
• Build and optimize modern data architectures using Databricks, Delta Lake, Spark, SQL,.
• and cloud-native technologies to enable high-performance analytics and trusted business.
• insights.
• Develop and maintain curated semantic layers, business metrics, and governed datasets.
• that power self-service analytics and conversational AI solutions such as Databricks Genie.
• and other natural language query platforms.
• Partner with business stakeholders across Sales, Operations, Manufacturing, Supply Chain,.
• Finance, and HR to translate business requirements into scalable data solutions and.
• reusable data assets.
• Enable business users to interact with enterprise data through natural language interfaces.
• by designing data models, metadata frameworks, business glossaries, and governance.
• standards that improve AI-generated insights and query accuracy.
• Collaborate with Data Scientists, Analytics Engineers, and BI developers to support.
• advanced analytics, predictive modeling, and AI-driven decision-making.
• Establish data quality, lineage, observability, and governance frameworks to ensure trusted,.
• secure, and compliant enterprise data assets.
• Design and implement enterprise-wide KPI frameworks and metric definitions to create a.
• source of truth across functional domains.
• Optimize data performance, reliability, and scalability while reducing technical debt and.
• improving platform efficiency.
• Support the development of AI-enabled analytics capabilities, including retrieval-augmented.
• generation (RAG), vector search, knowledge repositories, and semantic search.
• solutions that enhance data discovery and business productivity.
• Drive adoption of modern data engineering best practices including CI/CD, Infrastructure as.
• Code, automated testing, and data lifecycle management.
• Partner with leadership and analytics teams to advance Lumentum's vision of a centralized,.
• AI-enabled analytics organization.
• Degree in Computer Engineering, Computer Science, IT, or related fields.
• 10+years of hands-on experience as a Data Engineer or similar role.
• Strong SQL and data modeling skills, including Databricks, Delta Lake, Spark, SQL, and.
• cloud-native technologies.
• Strong analytical, troubleshooting, and problem-solving skills with the ability to support.
• production environments.
• Good communication, problem solving skills, and teamwork mindset.
• Excellent English proficiency (reporting to foreign national).

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Google Cloud Platform, Data Warehousing, Architecture, Assurance, English

ประเภทงาน:

งานประจำ

• Design, build, and maintain scalable and efficient data pipelines and ETL processes.
• Develop and implement data models, data warehouses, and data lakes.
• Build and maintain pipelines on Google Cloud Platform (GCP), including ingesting and converting files (e.g., CSV/JSON/Parquet) and loading them into BigQuery.
• Monitor and optimize the performance of our data infrastructure.
• Collaborate with cross-functional teams to identify and gather data requirements.
• Ensure data quality and integrity by implementing data validation and cleansing procedures.
• Troubleshoot and resolve data-related issues in a timely manner.
• Stay up-to-date with new technologies and best practices in data engineering.
• At least 3 years of hands-on experience in data engineering.
• Hands-on experience with GCP, particularly BigQuery, including building pipelines that convert/transform files and load them into BigQuery.
• Proven experience with ETL tools or frameworks (e.g., Airflow, dbt, Informatica, Talend).
• Solid understanding of data warehousing and lakehouse architecture.
• Proficient with SQL and one or more programming languages (e.g., Python, Scala).
• Experience working with cloud platforms, GCP preferred; AWS or Azure a plus (e.g., Redshift, Snowflake).
• Comfortable working independently and able to manage priorities in a contract role.
• Good command in English is preferred (reading, writing and speaking).

ทักษะ:

Business Development, Recruitment, Thai

ประเภทงาน:

งานประจำ

• Arup's purpose, shared values and collaborative approach has set us apart for over 80 years, guiding how we shape a better world.
• The Senior Plumbing/ Hydraulics Engineer is a client-facing role will be responsible for leading the hydraulic (plumbing) design and technical delivery of projects across a range of sectors. The role will provide technical leadership, maintain design quality, support project delivery teams, and work closely with the Building Services leadership group to deliver innovative and sustainable solutions.
• The Opportunity.
• Lead the planning, design and delivery of hydraulic engineering services across a broad range of building projects.
• Provide technical leadership and coordinate hydraulic design activities with engineers from other disciplines.
• Prepare hydraulic design calculations, specifications, reports, drawings and tender documentation.
• Deliver designs for domestic hot and cold-water services (potable and non-potable), recycled water systems, sanitary drainage and trade waste systems, rainwater collection, storage and drainage systems, stormwater management systems, etc.
• Prepare reports and presentations for clients, providing strategic advice and technical recommendations.
• Manage project programmes, budgets and quality outcomes for hydraulic engineering scopes.
• Act as project manager on smaller and medium-sized projects where required.
• Support business development activities, including client engagement, proposal preparation and identification of new opportunities.
• Mentor and supervise junior engineers and designers.
• At Arup, you belong to an extraordinary collective - in which we encourage individuality to thrive. Our strength comes from how we respect, share and connect our diverse experiences, perspectives and ideas.
• You will have the opportunity do socially useful work that has meaning - to Arup, to your career, to our members and to the clients and communities we serve.
• Is this role right for you?.
• Relevant tertiary qualification in Mechanical, Hydraulics, Civil or Building Services Engineering.
• Atleast 7-12 years' relevant industry experience in hydraulic/plumbing engineering within a consulting engineering environment.
• Demonstrated experience delivering building services hydraulic design across commercial, mixed-use, healthcare, aviation, industrial, data centre, transport or mission critical projects.
• Strong understanding of relevant Thai and international plumbing, water services and drainage standards.
• Chartered Engineer status (or actively working towards chartership) preferred.
• Excellent communication and stakeholder management skills, with the ability to engage effectively with both technical and non-technical audiences.
• A proactive and resilient approach, with strong leadership capabilities, a commitment to quality, and the ability to thrive in a collaborative, fast-paced environment.
• What we offer you.
• At Arup, we care about each member's success, so we can grow together.
• Guided by our values, we provide an attractive total reward package that recognises the contribution of each of our members to our shared success. As well as competitive, fair, and equitable pay, we offer a career in which all of our members can belong, grow and thrive - through benefits that support health and wellbeing, a wide range of learning opportunities and many possibilities to have an impact through the work they do.
• We are owned in trust on behalf of our members, giving us the freedom, with personal responsibility, to set our own direction and choose work that aligns with our purpose and adds to Arup's legacy. Our members collaborate on ambitious projects to deliver remarkable outcomes for our clients and communities. Profit Share is a key part of our reward, enabling eligible members to share in the results of our collective efforts.
• Different people, shared values.
• Arup is an equal opportunity employer that actively promotes and nurtures a diverse and inclusive workforce. We welcome applications from individuals of all backgrounds, regardless of age (within legal limits), gender identity or expression, marital status, disability, neurotype or mental health, race or ethnicity, faith or belief, sexual orientation, socioeconomic background, and whether you're pregnant or on family leave. We are an open environment that embraces diverse experiences, perspectives, and ideas - this drives our excellence.
• Guided by our values and alignment with the UN Sustainable Development Goals, we create and contribute to equitable spaces and systems, while cultivating a sense of belonging for all. Our internal employee networks support our inclusive culture: from race, ethnicity and cross-cultural working to gender equity and LGBTQ+ and disability inclusion - we aim to create a space for you to express yourself and make a positive difference. Discover more about life at Arup at www.arup.com/careers/your-life-at-arup.
• We are committed to making our recruitment process and workplaces accessible to all candidates. Please let us know if you need any assistance or reasonable adjustments throughout your application or interview process, and/or to perform the essential functions of the role. We will do everything we can to support you.
• Our Application Process.
• Please apply directly through our applicant tracking system. Shortlisted candidates will be contacted by Talent Acquisition to discuss next steps. Stay safe online - Arup will never ask for your bank details as part of our recruitment process.
• Arup does not accept unsolicited resumes from recruiters or employment agencies.