Senior Data Quality Engineer
Chicago, IL (Hybrid – 3 days onsite)
Overview
- Join a team building a modern data platform and take ownership of data quality from the ground up
- This role exists because there is currently no formal data testing framework in place—you’ll define and implement it
- Focused on automation, scalability, and reliability, not manual QA
What You’ll Do
- Design and build automated data quality frameworks from scratch
- Implement validation across data ingestion and transformation pipelines (ETL/ELT)
- Write production-level Python code to enforce data integrity
- Embed data testing into CI/CD pipelines to prevent downstream issues
- Work within a Databricks-based environment (Bronze/Silver/Gold architecture)
- Partner closely with Data Engineering to ensure trusted, production-ready data
What They’re Looking For
- 5+ years in data engineering, data quality, or similar
- Strong hands-on experience with Python + SQL (both required)
- Experience building or owning automated data testing frameworks
- Familiarity with tools like Great Expectations, DBT tests, or similar
- Solid understanding of data pipelines and transformation logic
- Experience integrating testing into CI/CD workflows
- Comfortable working in a greenfield, low-structure environment with high ownership
Additional Information
- This opportunity is unable to provide sponsorship now or in the future; candidates must be authorized to work in the U.S. without sponsorship (U.S. citizen or permanent resident).
If this sounds like a fit, apply now!