เงื่อนไขการค้นหา

ทักษะ:

SQL

ประเภทงาน:

งานประจำ

Build reports, dashboards, and visualizations that turn data into clear business insights. Work with existing data sets and BI tools to support reporting and decision-making. Partner with data engineers, analysts, and business stakeholders to understand reporting needs and deliver effective visualization solutions. Use available tools and AI-assisted features to improve productivity, automate routine tasks, and enhance dashboard development. Ensure dashboards are accurate, user-friendly, and aligned with business requirements. Support data validation and basic quality checks in col ...

ประสบการณ์:

4 ปีขึ้นไป

ทักษะ:

Architecture, Recruitment, Python, Cloud Computing, ETL

ประเภทงาน:

งานประจำ

• Developing batch, CDC and/or streaming data ingestion pipelines from multiple source systems.
• Implementing Bronze, Silver and Gold data layers, including data cleansing, transformation and standardisation.
• Developing reusable data pipelines and supporting data product implementation.
• Implementing data quality, reconciliation, validation and monitoring controls.
• Supporting data migration, integration testing, UAT and production release.
• Working with the architecture team to ensure solutions follow agreed cloud, security, governance and engineering standards.
• Supporting knowledge transfer and BAU handover.
• What We're Looking For.
• 4+ years of experience in data engineering or related roles.
• Strong experience in Databricks, Azure, SQL, Python/PySpark, ETL/ELT, Delta Lake, data modelling, data quality and CI/CD.
• Experience in financial services especially asset management or large-scale data transformation, would be advantageous.
• Experience in workong on an end-to-end enterprise data transformation, from source ingestion through to governed data products and business reporting.
• Experience in asset management company, fintech, or other regulated industries.
• Why Join CAPCO.
• Work on engaging projects with some of the largest banks/insurance in the world, on projects that will transform the financial services industry.
• Work in a collaborative, flat, and entrepreneurial consulting culture.
• Access continuous learning, training, and industry certifications.
• Be part of a team shaping the future of digital financial services.
• Help shape the future of digital transformation across FS & Energy.
• We offer.
• A work culture focused on innovation and creating lasting value for our clients and employees.
• Ongoing learning opportunities to help you acquire new skills or deepen existing expertise in our financial services offerings.
• A flat, non-hierarchical structure that will enable you to work with senior partners and directly with clients.
• An agile, diverse, entrepreneurial, inclusive, meritocratic culture.
• Joining Capco means joining an organisation that is committed to an inclusive working environment where you're encouraged to We celebrate individuality and recognize that diversity and inclusion, in all forms, is critical to success. It's important to us that we recruit and develop as diverse a range of talent as we can and we believe that everyone brings something different to the table - so we'd love to know what makes you different. Such differences may mean we need to make changes to our process to allow you the best possible platform to succeed, and we are happy to cater to any reasonable adjustments you may require. You will find the section to let us know of these at the bottom of your application form or you can mention it directly to your recruiter at any stage and they will be happy to help.
• We have been informed of several recruitment scams targeting the public. We strongly advise you to verify identities before engaging in recruitment related communication. All official Capco communication will be conducted via a Capco recruiter.
• LI-PW1.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Architecture, Recruitment, Apache, Python, English

ประเภทงาน:

งานประจำ

• Design, develop, and maintain scalable data pipelines for batch and real-time data processing.
• Build and optimize data ingestion, transformation, and loading (ETL/ELT) workflows.
• Work with Azure Data Services, Databricks, and Delta Lake to implement Lakehouse architecture.
• Ensure data quality, reliability, and availability across all data products.
• Collaborate with Data Architects to implement data models and architecture standards.
• Support data governance, metadata management, and lineage tracking.
• Ensure pipelines comply with PDPA, data classification, and security requirements.
• Monitor pipeline performance and troubleshoot data issues in production environments.
• Work closely with Data Scientists and Analysts to deliver model-ready datasets.
• Participate in code reviews and promote engineering best practices.
• What We're Looking For.
• 5+ years of experience in data engineering or related roles.
• Strong proficiency in SQL and Python for data transformation and processing.
• Hands-on experience with Azure Data Services, Databricks, and Delta Lake.
• Experience building and maintaining ETL/ELT pipelines at scale.
• Familiarity with data modeling concepts and distributed data systems.
• Understanding of data governance, data quality, and security practices.
• Proficient in Thai and English at intermediate level or above, sufficient for technical discussions,.
• meetings, and written documentation.
• Experience in banking, fintech, or other regulated industries.
• Knowledge of streaming technologies such as Apache Kafka or Azure Event Hubs.
• Familiarity with CI/CD practices and infrastructure-as-code for data pipelines.
• Exposure to Unity Catalog, Azure Purview, or similar metadata management tools.
• Experience working in Agile/Scrum environments.
• Why Join CAPCO.
• Work on engaging projects with some of the largest banks/insurance in the world, on projects that will transform the financial services industry.
• Work in a collaborative, flat, and entrepreneurial consulting culture.
• Access continuous learning, training, and industry certifications.
• Be part of a team shaping the future of digital financial services.
• Help shape the future of digital transformation across FS & Energy.
• We offer.
• A work culture focused on innovation and creating lasting value for our clients and employees.
• Ongoing learning opportunities to help you acquire new skills or deepen existing expertise in our financial services offerings.
• A flat, non-hierarchical structure that will enable you to work with senior partners and directly with clients.
• An agile, diverse, entrepreneurial, inclusive, meritocratic culture.
• Joining Capco means joining an organisation that is committed to an inclusive working environment where you're encouraged to We celebrate individuality and recognize that diversity and inclusion, in all forms, is critical to success. It's important to us that we recruit and develop as diverse a range of talent as we can and we believe that everyone brings something different to the table - so we'd love to know what makes you different. Such differences may mean we need to make changes to our process to allow you the best possible platform to succeed, and we are happy to cater to any reasonable adjustments you may require. You will find the section to let us know of these at the bottom of your application form or you can mention it directly to your recruiter at any stage and they will be happy to help.
• We have been informed of several recruitment scams targeting the public. We strongly advise you to verify identities before engaging in recruitment related communication. All official Capco communication will be conducted via a Capco recruiter.
• LI-PW1.

ประสบการณ์:

1 ปีขึ้นไป

ทักษะ:

Database Development, Microsoft Access, Microsoft Office, Visual Basic, Sharepoint

ประเภทงาน:

งานประจำ

will include but not limited to: Establish and maintain the project-wide Project Data Structure database and the corresponding guidelines and ensure that it is consistently applied throughout all relevant processes and tools across the project. Development and implementation of information management practices, including tools, guidelines and procedures. Assist stakeholders to define and understand their responsibilities in relation to information management. Engaging with stakeholders to identify areas in which effective information management can lead to overall business improvem ...

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:

Leadership Skill

ประเภทงาน:

งานประจำ

• Data.
• Integration Service Engineer.
• Join KBTG - where innovation drives impact! With a purposeful mission, collaborative spirit, and a positive attitude, we create fintech solutions that empower. Be part of the future!.
• Designs, builds, and manages integration solutions leveraging streaming platforms, APIs, data virtualization technologies, and modern agent communication frameworks (such as Model Context Protocol (MCP) and agent-to-agent (A2A) patterns) to enable seamless AI and ML integration within banking enterprise ecosystems.
• Establishes and enforces integration processes, design standards, governance frameworks, and reusable design patterns for seamless connectivity between diverse entities including banking applications, data platforms, ML models, AI agents, external APIs, and cloud-based services ensuring efficient data ingestion, routing, calculation, prediction, and storage across distributed cloud environments, local databases, and other applicable technologies.
• Develops and maintains event-driven and batch-based integration flows that connect banking systems, ML prediction services, and AI agents for intelligent automation and enhanced customer experience.
• Establishes governance controls for data access, agent interactions, and tool usage including authentication, authorization, auditability, and compliance with banking regulations and enterprise policies while implementing MCP-based connectivity and A2A communication patterns to securely expose banking tools, resources, and data to LLM-powered applications and enable multi-agent collaboration for complex workflows and compliance checks.
• Provides observation and monitoring capabilities combined with high availability, proactive troubleshooting, and continuous improvement for streaming pipelines, API endpoints, MCP tool calls, and A2A interactions to ensure reliability, performance, and compliance.
• Reviews business and technical requirements to recommend enhancements and upgrades for integration platforms, agent communication protocols, and AI/ML-driven data operations.
• May be internal or external, client-focused, working in conjunction with Professional Services and outsourcing functions.
• See also: AI/ML Engineer for responsibilities related to advanced model development and deployment.
• See also: Data Scientist for responsibilities related to data analytics, modeling, and insights generation.
• See also: Internet Systems for responsibilities related to network infrastructure and connectivity.
• Bachelor's or Master's in Computer Science, Computer Engineer, Information Systems, or related field.
• Strong experience with integration technologies: Streaming (Kafka/Event Hub), APIs, Data Virtualization (DV Composite), MCP, and A2A frameworks.
• Proficiency in cloud platforms (AWS, Azure, GCP) with advanced knowledge of networking concepts (VPC, VPN, load balancing, firewalls, secure connectivity).
• Expertise in authentication and authorization protocols (OAuth2, JWT, SSL/TLS) and secure integration practices.
• Knowledge of banking systems, regulatory compliance, and governance controls for data and agent interactions.
• Ability to design end-to-end integration flows connecting traditional systems and AI-driven components.
• Drive practically with passion.
• Innovate to beat the best and adaptable to change.
• Strong teamwork and open communication.
• Proactive, resilient, and optimistic mindset.
• Given the specialized nature of this role, only candidates with relevant expertise and proven domain knowledge will be considered.
• At KBTG, diversity fuels innovation. We embrace different perspectives, foster an inclusive culture, and create opportunities for growth. Be yourself, make an impact, and grow with us. Join us.
• Hybrid Working - Balance office collaboration and remote flexibility.
• Competitive Provident Fund - Secure your future with high contributions.
• Financial Wellness - Expert support and tools for managing finances, including home loans.
• Comprehensive Health Coverage - Enjoy peace of mind with top-tier health insurance and annual health check-ups for you, your spouse, and your children.
• Flexible Benefits - Customize your perks with generous policies, including support for work-from-home equipment, wellness, and more.
• Wellness & Comfort - Recharge in our Nap Room, enjoy occasional massages, and access mental wellness support via Occa.
• Business Travel & Commuting Support - Enjoy Grab for Business rides and other travel perks for professional journey with ease and convenience.
• Continuous Learning - Access Udemy, Coursera, and top training programs.
• K Point Reward - Earn points and enjoy exciting rewards as you grow with us.
• The.
• outlined above are subject to change in accordance with project demands and business needs.
• https://www.kbtg.tech/th/privacy-policy.

ทักษะ:

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

ประเภทงาน:

งานประจำ

The Data Engineer will design, build, and maintain scalable data infrastructure to support real-time analytics, robotics telemetry, and AI model training. This role is key to ensuring high data availability, integrity, and performance for subsea IRM operations. The ideal candidate is skilled in managing data pipelines that interface with both hardware systems and cloud platforms. Duties and Responsibility 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 analysi ...

ทักษะ:

Analytical Thinking, Product Development, Architecture, Recruitment, Javascript

ประเภทงาน:

งานประจำ

• Design, build, and maintain scalable ETL/ELT pipelines to ingest, transform, and serve data from CEG systems (case management, telephony, chat, bots, QA tools, WFM, CRM) and third party tools and logs.
• Develop and optimize data models (e.g., warehouse tables, marts, views) that power CEG reporting, monitoring, forecasting, QA, and experimentation.
• Implement validation checks, anomaly detection, and monitoring for key CEG datasets and metrics.
• Work with stakeholders to define and enforce data definitions, SLAs, and ownership for critical tables and metrics.
• Improve performance and cost efficiency of data jobs and queries (e.g., partitioning, indexing, query tuning, storage format optimization) for high volume CEG data (calls, chats, emails, cases, events).
• Collaborate with data platform and engineering teams to standardize tooling and best practices (e.g., version control, CI/CD for data and services, code review, documentation, runbooks).
• Data Tools & Product Development.
• Design and build data tools and internal products for CEG (e.g., self service analytics, case monitoring dashboards, alerting systems, investigator tools, QA/review tools, agent performance views).
• Use languages such as Python, Java, Golang, or JavaScript/TypeScript to implement APIs, data services, and lightweight UIs that expose data in a usable way to agents, managers, and operations teams.
• Work closely with CEG product managers and operations to translate operational pain points into concrete data tools, from problem framing to delivery and iteration.
• Apply solid software engineering practices testing, code reviews, CI/CD, observability to data products so they are reliable, maintainable, and easy to extend.
• At Staff level, define and drive the roadmap for key CEG data tools and platforms, ensuring reuse across regions, lines of business, and channels.
• Data Analytics & Business Impact.
• Partner with CEG product and business teams to translate questions into data problems and design clear analytic approaches.
• Build and maintain dashboards and reports (e.g., contact volumes, handling time, quality, customer outcomes, agent performance, spot alerts) that provide reliable metrics and self service access to data.
• Perform deep dive analysis to understand trends in contact patterns, customer issues, agent performance, and operational efficiency; identify root causes and propose practical, data driven recommendations.
• Define and maintain metrics and KPIs (e.g., CSAT, NPS, SLA, AHT, FCR, quality scores), ensuring consistent definitions across CEG teams and tools.
• Communicate findings in simple, business friendly language, including clear implications and recommended next steps.
• Stakeholder & Team Collaboration.
• Act as a trusted data partner for CEG stakeholders (operations leaders, product managers, WFM, QA, training, policy, and regional leadership).
• Work with other data engineers, analysts, and scientists to align on data standards, reusable components, and shared datasets for CEG.
• Mentor junior and mid level team members on data engineering, analytics, and software engineering best practices.
• Contribute to continuous improvement of team workflows (code reviews, testing, documentation, runbooks, knowledge sharing, incident reviews).
• At Staff level, influence cross team architecture and ways of working, making sure CEG's data ecosystem scales with business growth.
• Required.
• 8+ years working as a Data Engineer, Analytics Engineer, or Data Analyst in a data driven environment (Staff level typically 10+ or equivalent scope/impact).
• Strong SQL skills (complex joins, window functions, aggregation, query optimization).
• Experience with at least one major data warehouse / big data technology (e.g., BigQuery, Snowflake, Redshift, Hive, Spark, Vertica, StarRocks, or similar).
• Solid experience with ETL/ELT tools or orchestration frameworks (e.g., Airflow, dbt, internal frameworks).
• Proficiency in at least one programming language for data and services (e.g., Python, Java, Golang, Kotlin, or JavaScript/TypeScript).
• Experience building production grade data pipelines and/or data services with attention to quality, monitoring, and maintainability.
• Experience with BI / visualization tools (e.g., Tableau, Power BI, Superset, Metabase, Looker).
• Strong analytical thinking: comfortable framing business questions, exploring data, and turning results into clear insights.
• Ability to communicate complex topics in simple, concise language to non technical stakeholders.
• Preferred.
• Experience with event driven data (logs, clickstream, customer journey, contact flows, tracking data).
• Knowledge of data modeling techniques (e.g., dimensional modeling, Kimball, data vault, star/snowflake schema).
• Experience with A/B testing, experimentation platforms, or causal analysis.
• Familiarity with ML pipelines or working with data science teams (e.g., routing models, QA scoring, forecasting, recommendations).
• Experience in online consumer products, travel, e commerce, or marketplaces.
• Hands on frontend or backend development experience (e.g., building internal tools in React/Next.js, Node.js, or similar frameworks) used by operations or support teams.
• Prior experience in a Staff or Tech Lead role, driving technical direction and mentoring multiple engineers/analysts.
• sanfrancisco.
• Please review our Hiring Process Guidelines before your interview click here to learn how interviewing at Agoda works.
• Discover more about working at Agoda.
• Agoda Careers https://careersatagoda.com.
• Facebook https://www.facebook.com/agodacareers/.
• LinkedIn https://www.linkedin.com/company/agoda.
• YouTube https://www.youtube.com/agodalife.
• Equal Opportunity Employer.
• At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person's merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.
• We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy.
• Disclaimer.
• We do not accept any terms or conditions, nor do we recognize any agency's representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.

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 ...

ทักษะ:

Continuous Integration, Automation, DevOps, Cloud Computing

ประเภทงาน:

งานประจำ

Bachelor's degree in Computer Science, Information Technology, or related field. Experience with CI/CD pipelines and automation tools. Strong knowledge of cloud infrastructure and container technologies. Experience managing infrastructure for scalable applications or data workloads. Familiarity with infrastructure-as-code and system monitoring tools. Understanding of system reliability, availability, and security practices. Able to work onsite at SCG Bang Sue Head office.

ทักษะ:

node.js, Python

ประเภทงาน:

งานประจำ

• Design, develop, and integrate AI/ML models into scalable production applications.
• Build and maintain applications, APIs, and pipelines that support AI models.
• Write clean, maintainable, AI-first code and participate in code & model reviews.
• Optimize AI solutions for latency, reliability, scalability, and performance.
• Ensure production AI systems meet quality, availability, and compliance standards.
• Stay updated on AI/ML frameworks and best practices, suggesting improvements to systems and processes.
• Bachelor's or Master's degree in Computer Science, AI, Software Engineering, or related field.
• Strong programming skills in Python, Node.js, or similar languages.
• Experience building AI applications, APIs, and integrating AI/ML models into scalable systems.
• Experience with AI/ML frameworks, LLM frameworks, and model serving tools.
• Understanding of system performance optimization, scalability, and reliability.

ประสบการณ์:

1 ปีขึ้นไป

ทักษะ:

Instrument

ประเภทงาน:

งานประจำ

Vocational or bachelor's degree in electrical, instrumentation, or control engineering; 1+ years experience with electrical, instrumentation, control systems, BMS, or PMS; Knowledge of electrical installation, instrumentation, control panels, and signal systems; Testing and commissioning expertise; Planning, control, and coordination skills; Analytical problem-solving ability.

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Microsoft SQL Server, Problem Solving, Automation, Leadership Skill, Teamwork

ประเภทงาน:

งานประจำ

A good honors Degree, preferably at postgraduate level, in Computer Science, Software Engineering, Statistics, Mathematics or related disciplines. Experience in Big 4 or MNC Consulting firm or industry equivalent role. Minimum 2 years (Analyst) or 4 years (Consultant) of relevant experience. Strong experience in one or more of the following programming languages: Scala, Python, or R. Experience with one or more non-relational data stores such as Pivotal, Cloudera, Hortonworks, MapR, Oracle BDA. Experience with one or more relational data stores using SQL, Oracle DB, Microsoft SQL S ...

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Architecture, Leadership Skill, Big Data, Python, English

ประเภทงาน:

งานประจำ

• Architect and optimize high-throughput data pipelines and unstructured data processing frameworks to directly power the enterprise AI Foundation Platform.
• Co-own the vector infrastructure alongside the AI Engineer Specialist, ensuring optimized embedding storage, indexing strategies, and fast vector search retrieval.
• Build automated ETL/ELT pipelines capable of transforming raw enterprise data into AI-ready formats (chunking, metadata tagging, and cleaning).
• Data Governance, Metadata & Cataloging.
• Implement metadata pipelines for comprehensive data catalog and data dictionary services, including schema capture, lineage tracking, and audit logging.
• Enforce data governance, access controls, and privacy compliance across all data stores used for training, fine-tuning, and RAG retrieval.
• Design and maintain operational data lineage to ensure transparency and auditability of data flowing into production AI models.
• Advanced AI Component Integration.
• Develop and tune robust data ingestion pipelines for OCR, NLP processing, recommendation systems, and multi-modal AI inputs.
• Optimize data tiering and caching strategies to reduce latency and infrastructure costs for live enterprise AI workloads.
• Build secure, scalable data connectors linking legacy enterprise databases with modern LLM frameworks and autonomous agents.
• Collaboration & Data Excellence.
• Partner directly with the AI Engineer Specialist to ensure seamless data delivery for real-world, high-concurrency production deployments.
• Bridge traditional data engineering practices with modern MLOps, setting up automated data validation, quality checking, and drift detection at the data layer.
• Provide data-level expertise during architecture reviews, ensuring scalable data design patterns across the entire AI project lifecycle.
• Key Impacts.
• Ensure high-quality, AI-ready data ingestion at scale, dramatically reducing the time-to-market for enterprise AI assets.
• Establish a secure and compliant data foundation that guarantees enterprise data privacy during AI model interactions.
• Eliminate data bottlenecks in real-world production environments, ensuring sub-second latency for enterprise RAG and search systems.
• Transition traditional data warehouses and lakes into future-ready, graph- and vector-enabled AI data infrastructure.
• Master's or Bachelor's degree in Computer Engineering, Computer Science, Data Engineering, or a related technical field.
• 5+ years of experience in heavy-duty Data Engineering, Big Data, or Distributed Systems, with strong production experience in an AI/ML context.
• Proven track record of building large-scale data infrastructure supporting live, mission-critical applications.
• Technical & AI Data Framework Expertise.
• Deep experience in Python and SQL, alongside modern big data tools (e.g., Spark, Kafka, or cloud equivalents).
• Hands-on expertise in Vector Databases and unstructured data processing.
• Strong understanding of data chunking strategies, text extraction (OCR/NLP pipelines), and metadata orchestration.
• Familiarity with cloud data platforms (AWS/Azure/GCP) including managed data lakes, data warehouses, and cloud-native security/encryption.
• Real-world experience implementing data catalogs, schema evolution, and automated data quality monitoring.
• Leadership & Soft Skills.
• Excellent technical communication skills to align data pipeline designs with AI model engineering requirements.
• Strong analytical and problem-solving mindset, comfortable handling noisy, unstructured enterprise data under tight deadlines.
• Good verbal and written English communication skills for vendor engagement and cross-functional team collaboration.

ทักษะ:

Big Data, SQL

ประเภทงาน:

งานประจำ

Welcome! 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:

Agile Development, Recruitment, YouTube, Python, Kafka, Scala, Java, SQL

ประเภทงาน:

งานประจำ

• At Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.
• Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.
• No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you're ready to begin your best journey and help build travel for the world, join us.
• In Agoda's Back End Engineering department, we build the scalable, fault-tolerant systems and APIs that host our core business logic. Our systems cover all major areas of our business: inventory and pricing, product information, customer data, communications, partner data, booking systems, payments, and more. These mission-critical systems change frequently with dozens of releases per day, so we must employ state-of-the-art CI/CD and testing techniques in order to make sure everything works without any downtime. We also ensure that our systems are self-healing, responding gracefully to extreme loads or unexpected input. In order to accomplish this, we use state-of-the-art languages like Scala and Go, data technologies like Kafka and Aerospike, and agile development practices. Most importantly though, we hire great people from all around the world and empower them to be successful. Whether it's building new projects like Flights and Packages or reimagining our existing business, you'll make a big impact as part of the Back End Engineering team.
• The Opportunity.
• We are seeking a Principal Engineer to drive innovation across our AI-powered data experience and platform infrastructure.
• This role combines.
• leading the development of AI-powered data querying.
• enabling users to ask business questions in natural language and receive actionable insights .
• while shaping the evolution of our data quality tools, and analytical engines.
• such as StarRocks.
• As a senior technical leader, you will operate across AI, data infrastructure, and reliability domains, driving high-impact initiatives and serving as a key technical authority across the organization.
• This position is based in Bangkok, Thailand. (Relocation support is provided).
• Lead the development of.
• AI-powered data querying solutions., enabling users to ask business questions in natural language and receive actionable insights.
• Architect and develop scalable data quality tools.
• and frameworks to ensure reliable and trustworthy data.
• Act as a hands-on technical leader, tackling complex challenges.
• across AI query engines, data quality systems, and analytical engines.
• Collaborate with TPMs and stakeholders to define and.
• drive the technical vision and roadmap.
• for AI-driven querying, query engines, and data quality tools.
• Mentor engineers and raise standards.
• across data quality & governance tools, query engines, and the broader data platform.
• 10+ years.
• of experience in software engineering, data engineering, or related fields.
• SQL and large-scale data systems.
• Modern analytical databases / data warehouses.
• (e.g., StarRocks, Snowflake, BigQuery, ClickHouse).
• Backend development.
• (e.g., Python, Java, Scala or similar).
• AI/LLM-based applications.
• (e.g., text-to-SQL, conversational interfaces, cursor, copilots).
• Data platforms or.
• analytical infrastructure at scale.
• Strong understanding of.
• data modeling, query execution, and performance optimization.
• Proven ability to.
• lead cross-team, high-impact technical initiatives.
• Ability to navigate between.
• deep hands-on work and strategic technical leadership.
• Excellent communication skills with both technical and non-technical stakeholders.
• Experience with.
• text-to-SQL systems.
• or AI-driven data interfaces.
• Experience implementing or scaling.
• analytical engines.
• such as StarRocks.
• Background in.
• data observability, quality, or governance frameworks.
• Experience with tools like.
• dbt, Airflow, Spark, or similar.
• Bengaluru.
• Please review our Hiring Process Guidelines before your interview click.
• here.
• to learn how interviewing at Agoda works.
• Discover more about working at Agoda.
• Agoda Careers.
• https://careersatagoda.com.
• Facebook.
• https://www.facebook.com/agodacareers/.
• LinkedIn.
• https://www.linkedin.com/company/agoda.
• YouTube.
• https://www.youtube.com/agodalife.
• Equal Opportunity Employer.
• At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person's merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.
• We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy.
• Disclaimer.
• We do not accept any terms or conditions, nor do we recognize any agency's representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.

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.

ทักษะ:

Compliance, Civil Engineering, Electrical Engineering

ประเภทงาน:

งานประจำ

• Lead and manage all on-site construction activities for data center projects from start to completion.
• Site Supervision & Project Execution: Manage on-site engineering operations, ensuring all activities align with project plans, technical specifications, and timelines..
• Construction Quality & Safety Compliance: Ensure all construction activities comply with local and international engineering standards, regulations, and safety protocols..
• Coordination & Communication: Work closely with project team, contractors, consultants, and key stakeholders to ensure smooth project execution..
• Technical Review & Problem-Solving: Analyze engineering designs, reports, and specifications to identify and resolve technical issues efficiently..
• Progress Monitoring & Reporting: Track project milestones, prepare site reports, and provide updates to senior management and stakeholders..
• Material & Resource Management: Tracking, foreseeing, and addressing the availability of materials and key equipment to ensure smooth project execution..
• Stakeholder Liaison: Maintain effective communication with local authorities, subcontractors, and project teams to facilitate seamless operations..
• Job Qualifications.
• Bachelor's degree in Civil Engineering, Electrical Engineering, or related field or a related field.
• Minimum 3-10 years of experience in large-scale infrastructure or construction projects (experience in data center projects is a plus but not required)..
• Strong technical knowledge of power systems, cooling solutions, and network architecture.
• Strong leadership, problem-solving, and cross-cultural communication skills..

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).

ทักษะ:

ETL, SQL, Python

ประเภทงาน:

งานประจำ

• Responsible for the design, construction, and maintenance of optimal and scalable data pipeline architectures on cloud platforms (e.g., GCP, AWS, Azure).
• Oversee the development and management of complex ETL/ELT processes for data ingestion from a wide array of sources.
• Author and optimize advanced, high-performance SQL queries for complex data transformation, aggregation, and analysis.
• Leverage the Python programming language for automation, scripting, and the development of data processing frameworks.
• Administer and optimize cloud-based data warehouse solutions and associated data lakes.
• Collaborate professionally with data scientists, analysts, and key business stakeholders to ascertain data requirements and deliver effective technical solutions.
• Provide mentorship to junior engineers and champion the adoption of data engineering best practices throughout the organization.
• Bachelor's degree or higher in Computer Science, Information Technology, Engineering, or a related field.
• At least 5 years of experience working in a data engineering or related position.
• Proficient in advanced SQL, including query optimization and performance tuning.
• Experienced in managing and designing architecture on at least one major cloud platform (Google Cloud Platform, AWS, or Azure).
• Skilled in using Python for data processing and advanced pipeline development.
• Experienced with tools and technologies for data ingestion, connectivity, and management.
• Deep understanding of data modeling principles, data warehousing methodologies, and modern data architecture.
• Excellent analytical and problem-solving skills.
• Communication and teamwork skills.
• Ability to plan and manage tasks effectively.