Overview
Skills
Job Details
Data Analyst Data Validation Engineer
Temp to Hire
100% offsite - 8am-5pm EST
Visa: USC/ EAD
The ideal candidate brings 5+ years of data quality engineering experience with a strong analytical mindset and the ability to investigate datasets holistically understanding how data relates to itself and to adjacent datasets, formulating the right questions, and designing targeted analyses to uncover issues or validate accuracy. They should be proficient in Databricks and SQL Server testing environments, with hands-on experience using data validation frameworks such as Collibra or Great Expectations. Strong Python and SQL skills are essential for building data quality checks, along with expertise in data profiling and anomaly detection techniques. The candidate must be comfortable reading and interpreting code written by others, enabling them to trace identified data issues back to their source within pipeline logic and communicate findings clearly to engineering teams. Experience with test automation frameworks and quality process development is expected, and healthcare data validation experience is preferred. Strong documentation skills and the ability to define and track quality metrics round out the profile.
Skills: -
- Databricks and SQL Server testing
- Data validation frameworks (Colibra, Great Expectations)
- Test automation frameworks
- Python and SQL for data quality checks
- Data profiling and anomaly detection - Documentation and quality metrics
Experience: -
- 5+ years data quality engineering
- Healthcare data validation experience preferred
- Test automation and quality process development
Education
- Bachelors Degree or equivalent experience. Healthcare experience preferred
Manager s Additional Expectations (All Roles)
- Senior-level contributors who can operate independently with minimal direction
- Comfortable working with unclear or evolving requirements
- Not just task executors must separate what stakeholders ask for vs. what they actually need
- Strong communication skills; experience working with both clinical and non-clinical teams
- Ability to perform iterative validation cycles: review refine validate finalize
- Healthcare experience is preferred, but strong technical candidates from other industries may be considered
- Strong analytical thinker who understands how datasets relate
- Can trace data issues back through pipeline logic
- Skilled with documentation and defining measurable quality metrics
- Can build automated quality workflows and partner with engineering teams