Role: Databricks Engineer (with Validation/Testing experience)
Location: 100% remote (east coast hours)
Duration: 3-year project
Notes/Job Description:
The team is seeing many resumes that mention Databricks superficially, but they are specifically looking for a true Databricks expert—someone who knows the platform end‑to‑end, not just an analyst or light user.
This is a hands‑on engineering role, not an analytics position. The ideal candidate should be comfortable building custom utilities, writing Python and PySpark code, and troubleshooting complex data movement and validation issues independently.
Key Requirements
- Deep Databricks expertise (developer‑level), not just exposure
- Strong hands‑on experience with Databricks Medallion Architecture
- Bronze / Silver / Gold (also referred to as Raw / Silver / Mark layers internally)
- Experience validating and testing data as it moves across layers
- Experience ingesting data from 10+ source systems into data lakes
- Very strong with Databricks notebooks, Unity Catalog, Python, and PySpark
- Ability to test and report on curated data layers and clearly explain QA/testing approaches
- Experience with CI/CD in Databricks, including promotion of code vs. developer workflows
- Familiarity with Playwright and TypeScript for testing is nice to have
- Certifications are a plus, but not mandatory
Team & Process
- Role is embedded within the Enterprise Data & Analytics Platform team
- Must align with established QA and governance processes
Overall Takeaway They want a Databricks‑first engineer who has designed, built, tested, and operatedDatabricks pipelines in complex, multi‑source enterprise environments—not someone with Databricks listed as a secondary skill.