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We are seeking a Data QA / Validation Engineer (Contractor) to ensure data quality across Databricks / Spark / Delta Lake pipelines.
The role focuses on validating clean, accurate datasets that power downstream analytics, machine learning, and real-time decision-making systems.
You will design and implement automated data quality tests for ingestion and transformation layers (Bronze ? Silver ? Gold), enforce schema and data contracts, detect drift, validate feature pipelines, and monitor data anomalies.
Key Responsibilities
Develop and execute automated data quality tests for ingestion and transformation layers.
Enforce schema and data contracts across pipelines.
Detect and address data drift and anomalies.
Validate feature pipelines to ensure accuracy and reliability.
Monitor data quality and maintain issue logs for critical pipelines.
Deliver production-grade validation suites and provide QA sign-off for key data processes.
Required Qualifications
8+ years of experience in SQL.
5+ years of experience with Databricks and Spark.
3+ years of experience in data quality frameworks (e.g., Great Expectations, Deequ, Soda, dbt tests).
3+ years of experience using GenAI tools (Cursor, Windsurf, GitHub Copilot, Databricks Assistant) for test generation and validation workflows.
5+ years of experience delivering production-grade validation suites and QA sign-off for critical pipelines.