Sr. Data Quality Engineer ; _

Affinity Solutions is the leading consumer purchase insights company. We provide a complete view of U.S. and U.K. consumer spending, across and between brands, via exclusive access to fully permissioned transaction data from over 100 million consumers. Our proprietary AI technology, Comet™, transforms these purchase signals into actionable insights for business and marketing leaders to drive optimal outcomes and build lasting customer relationships.

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Affinity is seeking an accomplished Sr. Data Quality Engineer I to ensure the quality, reliability, and accuracy of data pipelines, APIs, integrations, and data products built by our software engineering teams. In this critical role, you will design and implement comprehensive quality testing frameworks, validate data integrity across complex systems, and partner with data engineers and software engineers to deliver trusted, high-performance solutions.

• Quality Testing and Validation
  • Design, develop, and execute comprehensive test strategies for data pipelines, APIs, integrations, and data products built by software engineering teams
  • Develop and maintain automated testing frameworks for API validation, data quality checks, integration testing, and end-to-end pipeline testing
  • Perform thorough testing of RESTful APIs, including functional testing, performance testing, security testing, contract testing, and integration testing with third-party vendors
  • Validate data accuracy, completeness, consistency, and timeliness across ETL/ELT pipelines, data warehouses, and data lake environments
  • Test data clean room implementations, privacy controls, query constraints, and secure data-sharing mechanisms to ensure compliance with security standards
  • Create and maintain comprehensive test cases, test data sets, and testing documentation for all quality assurance activities
• Data Pipeline and Integration Testing
  • Validate data transformations, aggregations, and calculations across Snowflake, AWS, and other cloud data platforms
  • Test integration pipelines, including Live Ramp XMI, Salesforce, AWS/AMC clean rooms, CAPI integrations, and Mad Connect to ensure seamless data flow and accuracy
  • Perform regression testing on data pipelines to ensure changes do not introduce data quality issues or break existing functionality
  • Validate data lineage and metadata accuracy and ensure proper implementation of data governance controls
  • Test database performance, query optimization, and data structure implementations to identify bottlenecks and ensure optimal performance at scale (200
    
    BIL+ records)
• Automation and Monitoring
  • Build and maintain CI/CD test automation pipelines using Jenkins and other Dev Ops tools to enable continuous quality validation
  • Implement automated data quality monitoring, anomaly detection, and alerting systems to proactively identify issues
  • Develop test harnesses and mock services for isolated component testing and integration validation
  • Create performance benchmarks and load testing scenarios to validate system scalability and reliability
  • Establish and track quality metrics, test coverage, defect rates, and SLAs to measure and improve testing effectiveness
• Compliance and Security Testing
  • Validate implementation of data privacy regulations (GDPR, CCPA, HIPAA) and ensure compliance across all data products
  • Test security measures, including data encryption, masking, tokenization, role-based access controls (RBAC), and authentication mechanisms (OAuth, JWT, SSO)
  • Verify proper implementation of data access controls including aggregation constraints, projection policies, row access policies, column masking, and differential privacy
  • Conduct security testing on APIs and integrations to identify vulnerabilities and ensure adherence to security best practices
• Collaboration and Documentation
  • Collaborate closely with senior data and software engineers (API and integrations) to understand requirements, identify test scenarios, and provide quality feedback early in the development cycle
  • Participate in code reviews, design discussions, and sprint planning to ensure quality is built into solutions from the start
  • Document test plans, test results, defects, and quality reports with clear, actionable insights for engineering teams
  • Provide technical mentorship to junior QA engineers and promote testing best practices across the organization
  • Partner with infrastructure teams to coordinate test environment setup and deployment validation
• Stay current with emerging testing technologies, tools, and methodologies in data quality, API testing, and test automation
• Identify opportunities to improve testing efficiency, reduce testing cycles, and enhance overall quality processes
• Lead proof-of-concept initiatives to evaluate new testing tools and frameworks (Great Expectations, Soda Core, Postman, REST Assured, etc.)
• Drive strategic recommendations to enhance data quality validation, testing coverage, and organizational…