Data Quality Automation Engineer

Data Quality Automation EngineerOur Randstad client in Washington, DC is seeking a Data Quality Automation Engineer to lead the design and implementation of automated data validation, profiling, and anomaly detection pipelines. This role will play a critical part in ensuring data integrity across modern data platforms including Databricks, SAP DataSphere, and Informatica Cloud. The ideal candidate will have strong technical skills in Python and SQL, a solid understanding of data governance, and experience working cross-functionally with engineering, governance, and business teams to embed quality and compliance into every stage of the data lifecycle.Key Responsibilities:Design and implement scalable, automated data quality pipelines to proactively identify and resolve data issuesBuild reusable components for anomaly detection, rule enforcement, and schema validationTranslate data governance policies (e.g., certified sources, critical fields) into enforceable technical rulesIntegrate quality checks across tools like Databricks, SAP DataSphere, and Informatica Cloud, while remaining adaptable to evolving tech stacksPartner with data engineers, governance teams, analysts, and product owners to align quality expectations and deliver trusted dataTrack, document, and report on data quality metrics, including rule compliance and issue resolutionLeverage tools such as Great Expectations or AWS Deequ to implement data quality frameworksUse Python and SQL to create profiling scripts and validation logicSupport enterprise adoption of certified datasets and enforce ownership and stewardship rules Samprasoft