Experience:

3 years required

Skills:

Google Cloud Platform, Cloud Computing

Job type:

Full-time

• Work directly with business users, product owners and project teams to listen to and clarify requirements and project objectives, and translate them into data architecture and solution designs.
• Design ingestion, storage, processing and data sharing solutions on Google Cloud, balancing performance, scalability, security and cost, and document design decisions and trade-offs.
• Produce data sizing and cost estimates for new projects and platform changes, and pr ...
• Work with the solution delivery manager and business analysts to join requirement sessions from the start, translate agreed requirements into technical design, and provide effort estimates, impact analysis and delivery plans for project, ad hoc and enhancement requests.
• Build & Delivery.
• Build and maintain batch and streaming pipelines using SQL, Python and GCP services, and manage transformation logic in Dataform on BigQuery.
• Develop Python and file transfer scripts (FTP / SFTP) to integrate external, partner and legacy source systems, and to automate recurring operational tasks.
• Implement data models, data quality, validation and reconciliation controls that meet functional and non-functional business requirements.
• Governance, Security & Operations.
• Implement access control, data classification and data sharing models so that each user group receives only the data appropriate to their role, and keep data secure and compliant across regions.
• Implement monitoring, logging, lineage and alerting so that pipeline issues are detectable, traceable and resolved within agreed service levels, and automate recovery where possible.
• Monitor and optimize cloud cost and workload performance, and apply AI tools to engineering and operational workflows to improve team productivity.
• Technical Leadership.
• Set and uphold engineering standards: design review, coding standards, CI/CD, metadata conventions and documentation.
• Mentor mid-level and junior data engineers, review their designs and code, and raise the technical capability of the team.
• Lead root cause analysis during incidents, and support developers, analysts and data scientists on data initiatives.
• Take accountability for the quality of all code and pipelines released to production, including work drafted with AI assistance, ensuring it is reviewed, tested, documented and maintainable.
• Bachelor's degree or higher in Computer Science, Computer Engineering, Information Technology, Information Systems, Statistics or another quantitative field.
• 5+ years of hands-on data engineering experience, including end-to-end delivery of enterprise scale data platforms or pipelines.
• Strong hands-on experience on Google Cloud is essential: BigQuery, Dataform, Cloud Storage, Cloud Composer / Airflow, Dataflow or Dataproc, Pub/Sub, Cloud Functions, Cloud SQL and IAM.
• Advanced SQL and data modeling for analytical workloads, with proven query and cost optimization on large data sets; experience with relational and NoSQL databases (e.g. Postgres, Firestore).
• Strong Python scripting for data processing, integration and automation, including file transfer over FTP / SFTP and scheduled or event driven file based interfaces.
• Proven experience designing data architecture and solutions directly from business requirements, including data sizing and cost estimation for new workloads.
• Able to estimate effort and plan delivery jointly with project managers and business analysts across project, ad hoc and enhancement work.
• Experience with workflow orchestration and modern ETL / ELT patterns, and with implementing data quality, validation and reconciliation.
• Experience implementing data security and governance: IAM, row and column level security, masking, data classification and controlled data sharing across teams or business units.
• Experience operating production pipelines: monitoring, alerting, lineage, incident resolution and ongoing cost optimization.
• Experience partnering with cross functional business and technical teams in a fast paced, changing environment.
• Working knowledge of other cloud platforms (AWS or Azure) and the ability to compare equivalent services and design across environments, which is valuable in a multi-cloud or hybrid landscape.
• Experience with big data and streaming ecosystems such as Spark and Kafka.
• Experience applying AI / GenAI to engineering workflows such as code generation, documentation, testing or support automation.
• Experience with data governance and catalog tools (e.g. Dataplex), Infrastructure as Code (Terraform) and CI/CD for data pipelines.
• Experience in retail or in an organization serving multiple business units.
• Professional certification such as Google Professional Data Engineer or Professional Cloud Architect, or an equivalent certification on another cloud platform.
• Strong communication skills: listens, asks the right questions, and explains technical matters clearly to business users and non-technical stakeholders. This role requires someone who works well with people, not only with systems.
• Business oriented: understands the objective behind a request and proposes better alternatives where appropriate.
• Collaborative and service minded when working with business units, project teams and internal colleagues.
• Resilient under pressure, delivering quality work across multiple parallel projects and tight deadlines.
• Adaptable and open to change in requirements, priorities, technology and organization.
• Leadership and ownership: drives work end to end, makes decisions, mentors others and leads by example.
• Analytical and detail oriented, disciplined in root cause analysis, and proactive in improving existing processes.
• Good command of English and Thai for cross functional communication and technical documentation.