Senior Databricks Data Engineer
Summary
Senior data engineer building and maintaining scalable Databricks/AWS lakehouse ETL and ELT pipelines, turning complex operational data into governed, reusable data products for analytics, AI, and ML. Core stack: Databricks, Spark, SQL, Python, Delta Lake, Medallion Architecture, and Unity Catalog.
Shape Databricks and AWS data foundations as a hands-on Senior Data Engineer building scalable pipelines and trusted data products.
This senior position transforms complex operational data into reusable products for analytics, AI, machine learning, and self-service decisions. You will develop lakehouse solutions with Spark, SQL, Python, Delta Lake, and Medallion Architecture. The work supports Tableau reporting, Databricks Genie, and Genie Code across enterprise functions.
Key Responsibilities:
- Design, test, and maintain scalable Databricks ETL and ELT pipelines
- Build Delta Lake solutions using Medallion Architecture
- Integrate structured and semi-structured enterprise data sources
- Optimize workloads, queries, tables, compute, and pipeline performance
- Implement orchestration, monitoring, reconciliation, and automated recovery
Requirements:
- Hands-on experience with Databricks, Spark, SQL, Python, and AWS
- Knowledge of dimensional models, star schemas, and standardized KPIs
- Ability to create curated, reusable business-ready data products
- Experience with Unity Catalog governance, lineage, and access controls
- Understanding of testing, version control, Git, and CI/CD processes
Apply Databricks, AWS, Spark, and Python expertise to build governed data products supporting enterprise analytics and AI.