About the Role
We are seeking a highly analytical and detail-oriented Data QA Engineer to ensure the quality, accuracy, and reliability of data platforms, pipelines, and reporting systems. The ideal candidate has strong SQL expertise, a solid understanding of data engineering concepts, and the ability to independently investigate data issues, validate complex data flows, and support data quality initiatives across the organization.
Key Responsibilities
- Validate data accuracy, completeness, and consistency across multiple systems and environments.
- Perform data quality testing for ETL/ELT pipelines, data warehouses, and reporting solutions.
- Design and execute test plans, test cases, and validation strategies for data-centric applications.
- Write complex SQL queries for data validation, reconciliation, and root cause analysis.
- Analyze and troubleshoot data discrepancies across source and target systems.
- Review, understand, and debug Python-based data pipeline code when necessary.
- Collaborate with data engineers, software engineers, analysts, and business stakeholders to ensure data integrity.
- Utilize AI-powered tools to improve testing efficiency, investigation, analysis, and productivity.
- Work independently and take ownership of data quality initiatives throughout the project lifecycle.
Required Skills
Database Engineering & SQL
- Strong knowledge of relational databases and database concepts.
- Data validation
- Data reconciliation
- Root cause analysis
- Data quality investigations
- Experience working with large datasets and optimizing data validation processes.
Data Infrastructure & Concepts
- Solid understanding of data engineering principles and best practices.
- Experience validating data pipelines and data processing workflows.
- Understanding of ETL/ELT architectures and data movement processes.
- Knowledge of data warehouse concepts and dimensional modeling.
- Familiarity with OLAP technologies and modern cloud data platforms such as Redshift, Snowflake, BigQuery, or equivalent.
Programming Skills
- Strong proficiency in Python.
- Ability to read, understand, analyze, and debug data pipeline code.
- Experience using Python for data validation, testing, or data analysis activities.
Additional Requirements
- Experience utilizing AI tools to improve testing, analysis, and productivity.
- Strong analytical thinking and problem-solving skills.
- Excellent attention to detail.
- Ability to work independently with minimal supervision.
- Strong communication and collaboration skills.
Nice to Have
- Experience with data quality f