Description

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/GCP, CI/CD.

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

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

Key Skills

Education

Bachelor's degree