Data Quality Engineer

Data Quality Engineer

• Strong Data Quality Engineering & Validation experience.

• Snowflake is mandatory – strong SQL, data profiling, tables/views, and query optimization.

• Experience with ETL/ELT pipelines, data warehouses, and large datasets.

• Strong understanding of data quality frameworks, including:

  • Data profiling & validation

  • Unit, integration & reconciliation testing

  • Completeness, accuracy, consistency, freshness & integrity checks

  • Data drift, duplicates, null patterns & business-rule validation

• Experience with source-to-target mapping, crosswalks, master/reference data, and reconciliations.

• Knowledge of Data Governance, metadata, lineage, audit & regulatory requirements.

• Ability to perform root-cause analysis and implement preventive controls.

• Experience building automated DQ checks, dashboards and reports.

• Preferred: Great Expectations, dbt tests, Informatica DQ, Talend DQ.

• Good to have: Python/PySpark, Azure/AWS/Google Cloud Platform, CI/CD.

• Domain experience in Healthcare, Finance, or other regulated industries is a plus.

• Strong analytical, communication, stakeholder-management, ownership, and problem-solving skills.