Description A leading infrastructure and transportation group is seeking a hands-on Senior Data Engineer to architect and build our next-generation Enterprise Reporting & Data Warehouse (ERDW.Next) on Databricks. Acting as the hands-on technical owner, you will drive target-state design, medallion architecture (Delta Lake), and legacy migrations off SQL Server/Synapse while remaining actively in the codebase. You will partner with our Enterprise Architect, Power BI team, business users, and offshore delivery partners across finance, construction, and safety domains.
QUALIFIED CANDIDATES SHOULD HAVE EXPERIENCE WITH:- Serving as a Databricks SME
- ERP integrations (strong plus)
- Python / PySpark
- Performance tuning and optimization
- Databricks maintenance, including VACUUM
- Data governance and best practices
- Semantic modeling
RESPONSIBILITIES- Architecture & Strategy: Design the ERDW.Next lakehouse (medallion/gold layer star schema) and govern data modeling, batch/streaming, and Delta Live Tables standards.
- Build & Migration: Write production-grade PySpark, Spark SQL, and Delta Live Tables pipelines orchestrated via Databricks Workflows. Re-engineer legacy SSIS/T-SQL/Synapse logic and ingest ERP data (JD Edwards, Anaplan) using CDC and Auto Loader.
- Platform Operations: Optimize cost/performance using Photon, Liquid Clustering, and OPTIMIZE. Manage CI/CD pipelines via Git and Databricks Asset Bundles while maintaining strict SLAs.
- Governance & AI: Implement Unity Catalog governance (entitlements, lineage, audit) and curate Databricks Genie Agents for natural-language analytics.
- Partner & Legacy Management: Support legacy platforms during transition and maintain code quality standards across offshore partner teams. Leverage agentic AI coding tools safely to accelerate delivery.
Requirements EXPERIENCE- Education: Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent practical experience.
- Track Record: 5+ years dedicated to Databricks/Apache Spark platforms and 8+ years overall in Data Engineering/BI. Proven experience taking an enterprise lakehouse end-to-end into production.
- System Experience: Deep hands-on experience migrating legacy warehouses (SQL Server, Synapse, ADF) and sourcing data from ERPs (JD Edwards strongly preferred).
- Certifications (Preferred): Databricks Certified Data Engineer Professional/Data Architect; Azure DP-203 or AZ-305.
TECHNICAL SKILLS- Databricks & Spark: Advanced PySpark, Spark SQL, Databricks Workflows, Delta Live Tables, Unity Catalog, Auto Loader, and Photon.
- Data Modeling & Storage: Star Schema, SCDs, Conformed Dimensions, Delta Lake (MERGE, Liquid Clustering, Z-ORDER, Time Travel).
- Cloud & DevOps: Azure Gen2, Key Vault, Entra ID, Git, Azure DevOps/GitHub Actions, Databricks Asset Bundles, and Infrastructure as Code (Terraform).
- Legacy & Integration: SQL/T-SQL, SSIS, SSRS, Synapse, ADF, CDC/replication tools, Direct Lake/Power BI integration, and Microsoft Fabric/OneLake.
- AI & Modern Workflow: Agentic AI coding tools, natural language query curation (Databricks Genie), and metadata-driven semantics.
SOFT SKILLS- Strong technical ownership, architectural influence, and clear communication with both executives and engineers.
- Excellent cross-functional collaboration with offshore partners, citizen developers, and business stakeholders.
- Pragmatic problem-solving, critical thinking, and time management across build and legacy support.
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