Data engineer with Snowflake

Key Responsibilities • Design, build, and operate end-to-end data pipelines (ingestion → transformation → serving) on Databricks and/or Snowflake, following medallion/layered architecture patterns • Configure and administer workspaces/accounts — compute policies, resource sizing, environment setup, and access hierarchy — per the SDP reference architecture • Implement data governance controls: catalogue and schema design, RBAC, row/column-level security, data masking, and lineage tracking • Set up CI/CD and infrastructure-as-code for pipeline deployment and environment promotion (dev → test → prod) • Configure monitoring, telemetry, and audit logging to meet SDP's central observability and security posture requirements • Support UAT, integration testing, and parallel-run validation during migration and go-live • Produce handover documentation (runbooks, access lists, escalation procedures) for agency operations teams • Work directly with GovTech's SDP Central Team, agency stakeholders, and Principal (Databricks/Snowflake) solution architects throughout delivery Required Technical Skills — Snowflake • Virtual warehouse sizing, scaling, and cost/performance tuning • Snowpipe and Snowpipe Streaming for continuous ingestion • Snowpark (Python/Scala) for in-warehouse data engineering • Role-based access control (RBAC), secure data sharing, and object tagging for governance • Query profiling and performance optimization (clustering keys, materialized views, caching) • Time Travel, zero-copy cloning, and Snowflake's native data protection features • Minimum 5 years of hands-on experience in Data Engineering, Data Platform Engineering, or related disciplines. • Minimum 3 years of hands-on experience with Snowflakes involving data pipeline Required Technical Skills — Common • Strong SQL and Python (PySpark or general-purpose) for data engineering • Data modeling — dimensional design, star/snowflake schemas, semantic layers • CI/CD pipelines (e.g., Azure DevOps, GitHub Actions, GitLab CI) for data engineering workflows • Infrastructure-as-code (Terraform preferred) for provisioning cloud data platform resources • Hands-on experience on at least one hyperscaler — AWS, Azure, or Google Cloud • Understanding of data security and compliance frameworks applicable to government/public-sector environments Preferred Qualifications • Databricks Certified Data Engineer Associate/Professional • SnowPro Core, or SnowPro Advanced: Data Engineer • Prior experience delivering on a government or regulated-sector data platform, or exposure to compliance frameworks such as IM8 is an add o n • Experience working as part of a System Integrator (SI) delivery team alongside a platform Principal is an add on