Senior Data Quality Engineer - Cloud​/CDGC - Onsite - Boston - No C2C

Andover, MA – Must be able to work onsite 4 days per week!

Data Quality Engineer

The Data Quality Engineer is a technical professional responsible for engineering and operationalizing data quality across the enterprise data ecosystem. This role works closely with data engineers, business stakeholders and governance teams to translate business and technical requirements into scalable test strategies, automated validation frameworks, monitoring capabilities, and data quality controls.

• The engineer will lead the design and implementation of data quality and automated testing frameworks and will support the implementation and operationalization of Informatica IDMC capabilities, including Data Quality and Cloud Data Governance & Catalog (CDGC).
• The role will leverage metadata, lineage, profiling, business rules, and governance capabilities to strengthen data quality, traceability, compliance, audit readiness, and controlled data delivery.
• Success in this role requires strong analytical and engineering skills, hands‑on test automation expertise, and the ability to embed quality controls throughout the data development lifecycle.
• The engineer will continuously identify opportunities to increase automation, expand test coverage, improve observability, reduce manual quality assurance activities, and responsibly apply emerging AI‑assisted capabilities to improve the efficiency and effectiveness of data quality engineering.

• Design, develop, and maintain scalable data quality and automated testing frameworks for data pipelines, transformations, data models, and published data products.
• Author and execute test plans, test cases, automated validation routines, and reconciliation processes that validate data integrity across environments and throughout the data lifecycle.
• Design and implement automated data quality controls, including completeness, accuracy, validity, consistency, uniqueness, timeliness, and reconciliation checks within the approved technology stack.
• Perform impact analysis on data model, pipeline, and transformation changes and validate data integrity following deployment.
• Lead investigation and root‑cause analysis of data quality defects, partnering with engineering and business teams to distinguish source‑data, transformation, modeling, integration, and consumption‑layer issues and drive appropriate remediation.
• Expand test coverage through functional, regression, integration, reconciliation, and data performance testing strategies appropriate to enterprise data pipelines and analytical workloads.
• Embed automated data quality and regression testing into CI/CD pipelines, establishing quality gates that identify defects before deployment and validate data integrity following release.
• Support the implementation and operationalization of Informatica Cloud Data Governance & Catalog (CDGC), leveraging metadata, lineage, business rules, and governance capabilities to strengthen data quality controls and traceability.
• Support and operationalize enterprise data standards, including definitions, naming conventions, quality rules, and stewardship processes, in partnership with Data Governance.
• Document and validate business‑critical data flows and maintain traceable test evidence to support audit readiness and compliance requirements.
• Establish data quality KPIs, thresholds, monitoring, alerting, and exception‑management processes for proactive detection of anomalies, errors, and unexpected changes in production data.
• Develop and drive adoption of automated regression testing, reusable validation components, and reconciliation patterns that can be applied consistently across data domains and platform layers.
• Evaluate and incorporate AI‑assisted capabilities into data quality engineering…