The Senior Data Engineer is the lead delivery role for structured data engineering in Databricks. This role owns lakehouse execution across bronze, silver, and gold; common data model implementation; SAP and manufacturing data modeling; curated outputs for reporting and AI/BI; and the transformation layer that supports forecasting, process automation, and internal applications. This role is the core engineering owner for turning source data into governed, reusable, high-value data products and brings working knowledge of source integration patterns so engineering decisions remain practical from ingestion through consumption.

Works closely with architecture, BI, master data, product, and application teams to turn business requirements into trusted datasets and scalable data products. Coordinates with integration-focused resources on source readiness, connector behavior, and new source onboarding.

#IND1

• Lead Databricks lakehouse execution across bronze, silver, and gold with a focus on maintainable Lakeflow-driven pipelines and high-quality curated outputs.
• Own common data model implementation, conformed dimensions, fact design, and reusable gold datasets for reporting, forecasting, and AI/BI consumption.
• Design and build scalable data models for SAP, manufacturing, finance, sales, supply chain, and operational domains.
• Partner on source onboarding and ensure new data is shaped into governed medallion outputs that are usable for analytics and AI.
• Implement data quality checks, reconciliation logic, documentation, and performance optimization across structured data assets.
• Provide technical leadership for engineering backlog execution, code quality, testing discipline, and repeatable delivery standards in Databricks.

• 7+ years of experience in data engineering with strong ownership of Databricks, data modeling, and production data pipelines.
• Deep experience with Spark, SQL, Python, medallion architecture, and dimensional or conformed data model design.
• Experience working with SAP or comparable ERP data and complex manufacturing, finance, supply chain, or commercial subject areas.
• Experience building governed curated datasets for BI, forecasting, and AI enablement.
• Strong understanding of ETL/ELT patterns, source-to-target mapping, data quality, and performance optimization.
• Experience with Lakeflow, Fivetran-fed source patterns, Unity Catalog governance, and Power BI semantic consumption, preferred.
• Experience supporting AI/BI readiness, trusted metrics, and curated outputs for natural-language analytics, preferred.
• Exposure to observability, CI/CD, and testing frameworks in Databricks, preferred.