Databricks Data Engineer

**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 client, agency stakeholders, and Principal (Databricks/Snowflake) solution architects throughout delivery **Required Technical Skills — Databricks** * Unity Catalog — catalogue/schema design, access control, and data lineage * Lakeflow / Delta Live Tables for pipeline orchestration; Delta Lake table format * Databricks SQL and cluster/workspace administration (compute policies, pools, cost management) * Databricks Asset Bundles (DABs) and Databricks Repos for CI/CD * PySpark / Spark SQL for large-scale data transformation * Working knowledge of Databricks system tables (audit logs, billing/usage, query history) for observability * Minimum 5 years of hands-on experience in Data Engineering, Data Platform Engineering, or related disciplines. * Minimum 3 years of hands-on experience with Databricks involving data pipeline development, platform administration, governance, and optimization. **Required Technical Skills** * 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 on * Experience working as part of a System Integrator (SI) delivery team alongside a platform Principal is an add on