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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 responsibilities including designing tests, analyzing data structures, and collaborating with data teams. Experience in data warehousing and cloud platforms is beneficial.
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 and Python
Experience in data warehousing and cloud platforms
Technical skills: SQL (complex queries), Python (Pandas, PySpark), Data Warehousing (DWH), Cloud Platforms (AWS, Azure, GCP), BI Tools (Tableau, Power BI)
Analytical skills: Strong problem-solving, attention to detail, understanding data modeling, data lifecycle, and governance
Methodologies: Familiarity with data testing processes, data governance, and CI/CD