Staff Data Engineer

B.S. in Computer Science or equivalent experience. 8+ years building and operating production data platforms. 4+ years deep, hands-on Databricks/Spark (PySpark + SQL). Proven ownership of a production lakehouse (S3 + Delta Lake) with strict SLAs and compliance requirements. Expertise with Delta Lake (MERGE/CDC, schema evolution, time travel, OPTIMIZE/Z-ORDER, VACUUM) and DLT, Workflows, Auto Loader. Feature Store experience in production. Strong data modeling (dimensional, canonical), SCD Types 1/2, and handling slowly changing entities and schema drift. Track record delivering trustworthy datasets with monitoring, alerting, lineage, and clear documentation. Able to define and maintain metric layers consumed by product and business. Advanced Python and SQL. Testing culture (pytest), CI/CD (GitHub Actions), and Terraform for Databricks. Solid Git practices. AWS foundations: S3, IAM, networking basics; event ingestion. Excellent communication and leadership skills. Able to drive design reviews, write clear technical docs, and mentor engineers in a remote, async environment.

Implement new technologies aligned with business goals. Drive development from concept to market. Define lakehouse architecture and standards on Databricks. Build and operate high-reliability streaming and batch pipelines. Design medallion data models and canonical domains. Establish data quality, SLAs/SLOs, lineage, and audit-ready documentation. Drive analytics by defining and governing KPIs/metrics. Optimize cost/performance on Databricks. Enforce security and privacy controls. Enable self-serve with standardized datasets. Champion software excellence through Git, code reviews, testing, CI/CD, and IaC. Collaborate with product managers, designers, and stakeholders. Stay current with the latest technologies. Perform various engineering-related tasks.