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The Data QA Engineer role focuses on ensuring data reliability and accuracy through testing data pipelines and ETL processes. Candidates should have strong skills in SQL and Python, with experience in data warehousing and cloud platforms. Responsibilities include designing tests, analyzing data structures, and collaborating with stakeholders to maintain data integrity.
Job Responsibility:
Designing and running tests for data ingestion, transformation (ETL/ELT), and storage (data warehouses/lakes)
Analyzing data structure, identifying anomalies, and setting up continuous monitoring for quality issues
Building automated test frameworks using Python, Pytest, and SQL to catch defects early
Creating and implementing data quality rules and metrics (e.g., completeness, accuracy)
Working with data engineers, analysts, and business stakeholders to understand needs and resolve defects
Requirements:
Strong skills in SQL (complex queries)
Strong skills in Python (Pandas, PySpark)
Experience in Data Warehousing (DWH)
Experience with Cloud Platforms (AWS, Azure, GCP)
Experience with BI Tools (Tableau, Power BI)
Strong problem-solving
Attention to detail
Understanding of data modeling, data lifecycle, and governance
Familiarity with data testing processes, data governance, and CI/CD