Data Quality Engineer (Contractor)

About the Role

We are seeking an experienced Data Quality Engineer Contractor to ensure the accuracy and integrity of our critical data assets. This role is exciting as you will directly impact the reliability of our reporting, dashboards, and AI/ML model inputs through rigorous testing and validation.

Responsibilities

• Develop, maintain, and execute comprehensive data testing approaches, including validating sources and transformation logic.
• Design, execute, and maintain regression tests covering data quality, aggregation rules, and business logic validation.
• Identify root causes for data quality defects and implement sustainable countermeasures.
• Monitor reporting and BI dashboards (e.g., Tableau) to proactively identify anomalies and inconsistencies.
• Develop and maintain automated test scripts for data validation, primarily using Python-based frameworks.
• Write complex SQL queries to validate data integrity and ensure analytical outputs meet business requirements.
• Partner with data engineers and BI developers to verify model accuracy and analytical component integration.
• Support the validation of AI/ML models by testing input/output integrity.

Requirements

• Proficiency in writing complex SQL queries, joins, and aggregations for analytical validation.
• Hands-on testing experience with data quality/integrity frameworks such as Great Expectations.
• Strong Python experience for scripting, data validation, and automation tasks.
• 2 or more years of experience in Quality engineering focused on data testing, analytics validation, and BI/ETL systems.
• Exposure to BI/analytics tools such as Tableau or Power BI.
• Knowledge of Agile methodologies (Scrum/Kanban) and strong communication skills for stakeholder collaboration.
• Ability to develop deep domain knowledge of relevant business data models.

Nice-to-Haves

• Experience with DBT best practices.
• Familiarity with Semantic Layer tools (e.g., Metric Flow, Cube, DataPlex).