Description

You will own data quality investigations and validation across complex datasets.

Responsibilities

• Investigate datasets holistically, relating data to adjacent sources and formulating analysis questions.
• Design and execute targeted analyses to uncover data issues or validate accuracy.
• Build and implement data quality checks using Python and SQL.
• Trace identified data issues back to pipeline logic by reading and interpreting existing code.
• Define and track data quality metrics and document findings for engineering teams.

Required Skills

• 5+ years of data quality engineering experience.
• Proficiency in SQL and Python for data quality checks.
• Hands-on experience with Databricks and SQL Server testing environments.
• Experience using data validation frameworks such as Collibra or Great Expectations.
• Expertise in data profiling and anomaly detection techniques.
• Experience with test automation frameworks and quality process development.
• Strong ability to read and interpret code written by others.
• Familiarity with Big Data concepts.

Key Skills

Education

Any Gradute