Overview
The QA Data Test Engineer will play a pivotal role in a major data modernization initiative for a prominent international retail organization. This hands-on position involves taking ownership of data quality and automated testing as the company transitions from legacy SQL Server systems to a contemporary Snowflake and dbt ecosystem. The engineer will work closely with Data Engineers, Business Analysts, and Product Owners to ensure high data integrity, supporting critical business functions like Finance, Operations, HR, and Commercial activities.
Responsibilities
- Design and execute the test strategy for a modern cloud-based data platform.
- Build and maintain automated data quality, regression, and reconciliation test suites.
- Validate data migrations from legacy SQL Server environments into Snowflake.
- Develop row-level, column-level, and aggregate-level reconciliation checks.
- Create and maintain dbt tests across staging, transformation, and reporting layers.
- Integrate testing into CI/CD pipelines to ensure quality gates are enforced.
- Investigate data quality issues and support root cause analysis.
- Support UAT activities and production releases.
Requirements
- Proven experience as a QA Engineer, Test Engineer, or Data Quality Engineer within modern data environments.
- Strong SQL skills with the ability to write complex validation and reconciliation queries.
- Experience testing data warehouses, ETL/ELT pipelines, and analytical platforms.
- Hands-on experience with Snowflake, Azure, Databricks, or similar cloud data platforms.
- Experience with dbt testing frameworks.
- Knowledge of automated testing approaches including Great Expectations, Soda, dbt tests, or custom frameworks.
- Experience integrating testing into Azure DevOps, GitHub Actions, or similar CI/CD pipelines.
- Strong understanding of data lineage, data quality, and data governance principles.