Job Description
-Define and implement data quality rules (completeness, accuracy, consistency, timeliness)
-Develop and manage data contracts (schema, required fields, formats, constraints)
-Embed data quality checks directly into pipelines using SQL and PySpark
-Perform source-to-target validation during onboarding and migration
-Identify, analyze, and resolve data quality issues across data layers
-Build reusable data validation components and frameworks
-Create data quality metrics, reports, and monitoring
-Work closely with data engineers to ensure DQ is part of pipeline design, not post-processing
-Support governance initiatives including metadata, tagging, and lineage

-Pay rate between 50-65/hr

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified ca...