Senior Data QA Engineer

Position Summary

We are seeking a highly skilled and detail-oriented Senior QA Engineer with a strong background in data testing to join our QA team. This role will be responsible for ensuring the quality, accuracy, integrity, and completeness of data across our systems, pipelines, and integrations. The ideal candidate will have deep experience in testing data-heavy applications, databases, ETL processes, and data validation in BI/reporting tools.

Key Responsibilities

• Develop and execute comprehensive test plans and test cases focused on data validation, transformation, and integrity.
  
  

• Design and maintain test strategies for data pipelines, data warehouses, and ETL/ELT processes.
  
  

• Write complex SQL queries to validate data accuracy, consistency, and performance.
  
  

• Collaborate with data engineers, analysts, and developers to identify data quality issues and enforce data quality standards.
  
  

• Perform regression, smoke, and exploratory testing on analytics dashboards and reporting systems.
  
  

• Automate data validation tests where feasible using frameworks such as Pytest, dbt tests, Great Expectations, or similar tools.
  
  

• Participate in code reviews and continuous integration pipelines to support data quality enforcement.
  
  

• Provide leadership and mentorship to junior QA team members on best practices for data testing.
  
  

• Document test coverage, test results, defects, and overall test health in tools such as Jira, TestRail, or equivalents.
  
  

Required Qualifications

• 5+ years of experience in QA or software testing, with at least 2 years focused on data testing.
  
  

• Strong proficiency in writing and optimizing SQL for data validation.
  
  

• Experience testing ETL pipelines, data lakes, or data warehouse systems (e.g., Snowflake, BigQuery, Redshift).
  
  

• Familiarity with data testing tools like Great Expectations, dbt tests, QuerySurge, or custom Python scripts.
  
  

• Experience working with BI tools (e.g., Tableau, Power BI, Looker) to validate data presentation accuracy.
  
  

• Solid understanding of software testing principles and defect lifecycle.
  
  

• Familiarity with test automation frameworks and CI/CD practices.
  
  

Preferred Qualifications

• Experience with cloud platforms (AWS, GCP, or Azure) and cloud-native data tools.
  
  

• Familiarity with data governance, data lineage, and data privacy concepts.
  
  

• Programming skills in Python for test automation and scripting.
  
  

• Exposure to big data technologies (e.g., Spark, Hive, Kafka) is a plus.
  
  

Soft Skills

• Strong analytical thinking and attention to detail.
  
  

• Excellent communication and collaboration skills.

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  Comfortable working cross-functionally with engineering, product, and data teams.