Database Engineer - Databricks
Role details
Job location
Tech stack
Job description
- Own day-to-day operation and reliability of Databricks jobs, pipelines, compute/cluster configuration, Delta Lake tables, and SQL warehouses.
- Develop and optimize Spark transformations across bronze/silver/gold medallion layers including incremental loads via Auto Loader and Structured Streaming.
- Administer governance and access through Unity Catalog consistent with PII containment in a regulated lending environment.
- Monitor and control DBU consumption and cluster costs through alerting and right-sizing to keep platform spend predictable.
- Diagnose and resolve pipeline failures, data quality issues, schema drift, and connectivity problems end-to-end while maintaining runbooks and documentation.
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Requirements
Do you have experience in Spark?, * 3+ years of hands-on data engineering experience in a production environment.
- Deep Databricks expertise including notebooks, Jobs, Workflows, Unity Catalog governance, and Databricks Certification.
- Strong Python, PySpark, and SQL skills for building and debugging distributed data transformations.
- Solid MSSQL/SQL Server experience with focus on query optimization, indexing, and performance diagnostics.
- Production experience with Apache Airflow - authoring, scheduling, and debugging DAGs.
Benefits & conditions
- Competitive salary up to $150,000 annually.
- Working for one of the most trusted names in financial services for more than 100 years, a brand known by millions.
- Flexibility and work-life balance.
- Working on a caring and supportive team that values your input, shares your goals, and celebrates your success.