Title: Data Quality Validation Test Engineer
Length: 12 month contract
Location: Hybrid Atlanta (must be local to the area and able to work onsite 3 days/week)
USC/GC
Key Responsibilities
- Work in large-scale complex data ecosystems (warehousing integration engineering) to ensure data quality and accuracy across pipelines.
- Read and interpret data models source-to-target mappings and transformation logic.
- Design and implement Data Quality Validation frameworks including:
- Schema consistency checks
- Data integrity validations
- Transformation and mapping validation
- Row-level and aggregate reconciliation
- Develop and maintain automated data validation tests integrated into CI/CD pipelines (Azure DevOps GitHub Actions).
- Implement data quality gates to detect and block deployments with invalid data (null values schema drift unexpected row counts).
- Collaborate with Data Engineers and DevOps teams to ensure test environments mirror production for consistency.
- Integrate reporting tools and dashboards to provide real-time test outcomes and observability.
- Support and enhance ETL/ELT workflows ensuring robust orchestration and monitoring.
Required Skills & Experience
- Strong background in SQL and Python for data validation and automation.
- Hands-on experience with CI/CD pipelines using GitHub Actions and Azure DevOps.
- Understanding of ETL/ELT workflows data pipeline orchestration and data observability.
- Experience with data engineering platforms: Snowflake Databricks or Microsoft Fabric.
- Proven experience in automated data validation frameworks including real-time quality checks.
- Ability to design and maintain data quality gates that safeguard production pipelines.
- Experience working with DevOps and Data Engineering teams to ensure smooth integration and deployment.
Preferred Qualifications
- Experience in large enterprise environments with complex business models and data systems.
- Familiarity with reporting/visualization tools for surfacing data quality metrics.
- Strong problem-solving skills with an ability to debug troubleshoot and optimize data validation processes.