Data QA Engineer

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.
• Advanced SQL skills with the ability to write complex queries for:
  • 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 frameworks and monitoring tools.
• Experience in testing cloud-based data platforms.
• Knowledge of Apache Airflow, dbt, Spark, or similar data technologies.
• Experience working in Agile/Scrum environments.
• Familiarity with CI/CD practices for data engineering projects.