Data QA Engineer

Data QA Engineer

You will be responsible for designing and executing automated and targeted manual tests to validate data pipelines, transformations, models, and business intelligence outputs This role empowers the business to make confident, data-driven decisions by safeguarding the accuracy and trustworthiness of our data engineering deliverables.

Details

• Track record of working effectively in a remote, distributed team environment

Day-to-day

• Design, develop, and maintain automated data quality tests for ETL/ELT pipelines and analytical data models
• Perform in-depth manual verification on high-impact data flows, reports, and dashboard outputs
• Implement robust data quality monitoring, alerting, and validation frameworks to catch anomalies early in the data lifecycle
• Collaborate with data engineers and analysts to understand business

You bring

• And translate them into effective QA processes
• Thoroughly validate data transformations, aggregations, and outputs to uphold integrity and consistency
• Create clear, detailed documentation and actionable reports on data quality issues and improvements
• Continuously refine QA strategies and tools to adapt to the evolving data landscape and best practices
• Expertise in designing and implementing automated data testing solutions for data warehouses, data lakes, or large-the team ETL/ELT pipelines
• Strong experience with SQL and scripting languages such as Python for data validation and testing automation
• Solid understanding of data modeling concepts and BI/reporting tools

Bonus

• Experience with cloud-based data platforms (e.g., Snowflake, BigQuery, Redshift) and modern orchestration tools (e.g., Airflow, dbt)
• Knowledge of data governance, privacy standards, and compliance best practices
• Background in validating data for machine learning, analytics, or complex business reporting environments