Data Quality Engineer

Responsibilities

• Design, develop, and implement scalable automated data quality testing frameworks utilizing Python, PyTest, Great Expectations, dbt Tests, and related technologies.
• Develop complex SQL queries to perform data profiling, reconciliation, validation, root-cause analysis, and anomaly detection across enterprise datasets.
• Build automated validation processes throughout ETL/ELT pipelines to ensure data integrity from ingestion through transformation and consumption.
• Partner with Data Engineering teams to integrate data quality checks into CI/CD pipelines using Azure DevOps, GitHub Actions, Airflow, or similar automation platforms.
• Develop and maintain data observability solutions to monitor data freshness, schema drift, completeness, and production anomalies.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, Mathematics, or a related technical discipline required.
• 5+ years of experience in Data Engineering, Data Quality Engineering, Analytics Engineering, or a related data-focused role.
• Proven experience building automated data testing frameworks using Python, PyTest, Great Expectations, dbt Tests, or similar technologies.
• Advanced SQL skills with experience performing complex validation, reconciliation, profiling, and data analysis.
• Strong understanding of ETL/ELT architecture, modern data pipelines, and cloud data platforms.
• Proficiency in Python for automation, scripting, and integrating quality validation into enterprise workflows.
• Experience integrating automated testing into CI/CD pipelines utilizing Azure DevOps, GitHub Actions, Airflow, or similar platforms.

Pay

Salary Range: $130,000 - $140,000 annually depending on experience

Benefits

• Comprehensive Benefits: PTO, Paid Holidays, Medical, Dental, Vision, 401k, and Sick Leave as required by law.