Data Engineer

Responsible for supporting and evolving the Azure Databricks Lakehouse architecture of an established Data Warehouse team setting design standards, governing the platform, unlocking full Databricks/Databricks AI capabilities, and optimizing solutions for performance, cost, security, and scalability. What will your job look like? You will act as the technical design authority for an existing Databricks ETL team, working alongside customer business, development, Databricks, and DevOps teams. You will support and evolve the production Lakehouse architecture: Delta medallion layers, Databricks SQL Warehouses, Unity Catalog security, and data lineage. You will define and enforce design standards, reusable patterns, and best practices across the existing pipeline estate and all new development You will design new ingestion, streaming, and batch pipelines and review team designs against the medallion (bronze/silver/gold) architecture. You will drive continuous optimization of the running platform: cluster sizing, autoscaling, Photon usage (if decided), query performance, Delta Liquid Clustering/Z-Ordering, VACUUM strategies, and DBU cost governance You will translate business questions into analytical models, KPIs, and reusable semantic layers. You will mature CI/CD (Azure DevOps/GitHub), observability, and security (RBAC, row/column-level policies) across existing pipelines. You will evaluate and drive adoption of new Databricks capabilities (Lakeflow, Delta Live Tables, serverless compute, AI/BI) where they add value. You will conduct architectural reviews, code audits, and mentoring sessions to raise the team s engineering bar and ensure adherence to standards and scalability. You will guide the team in version control, automated testing, and release discipline for Databricks notebooks, jobs, and workflows.

Bachelor s degree in computer science, Information Technology, or related field Strong hands-on knowledge of Azure Databricks and the Azure platform, with proven experience operating a production Lakehouse at scale Proficiency in Databricks SQL, Python, and other relevant programming languages. Deep Azure knowledge: ADLS Gen2, Key Vault, Networking (VNet/Private Endpoints), Event Hub Deep understanding of advanced data warehouse concepts (dimensional modeling, SCD, surrogate key management) is required Experience with data modeling, dimensional modeling, and temporal data structures in an operational ETL environment Unity Catalog security & lineage. Strong business problem framing and stakeholder communication. Experience establishing engineering standards, performing design/code reviews, and mentoring data engineers Excellent problem-solving and communication skills Ability to work independently and collaboratively in a fast-paced environment.

You will support the architecture of a business-critical Databricks Lakehouse, shape how an established ETL team builds and operates data products, and work with the latest Azure Databricks technologies to deliver scalable, high-performance solutions.