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.

Affinity Solutions is seeking an accomplished Senior Data Quality Engineer to spearhead critical initiatives ensuring the accuracy, reliability, and compliance of Affinity's enterprise data ecosystem. In this strategic role, you will architect and implement sophisticated data quality frameworks, optimize data pipelines, and partner with cross‑functional teams to deliver trusted, high‑performance data solutions that drive business value. The ideal candidate combines deep technical expertise with proven leadership capabilities and a strategic vision for advancing data quality and governance maturity.

• Data Quality Strategy & Leadership
  • Establish and enforce enterprise‑wide data quality standards, frameworks, and best practices aligned with organizational objectives
  • Lead comprehensive data quality initiatives to monitor, validate, and enhance data accuracy, completeness, consistency, and timeliness across all systems
  • Design and implement automated data quality validation, profiling, and anomaly detection mechanisms
  • Define and track key data quality metrics and SLAs to measure and improve data reliability
  • Implement data quality gates and validation checkpoints throughout the data lifecycle
• Data Governance & Compliance
  • Develop and maintain comprehensive metadata repositories, data dictionaries, and data lineage documentation to ensure transparency and traceability
  • Ensure strict adherence to data privacy regulations (GDPR, CCPA, HIPAA) and industry compliance standards
  • Implement and enforce robust security measures including data encryption, masking, tokenization, and role‑based access controls
  • Participate in data governance committees and contribute to policy development
• Partner closely with data scientists, analytics engineers, platform engineers, and business stakeholders to deliver reliable, fit‑for‑purpose data solutions
• Provide technical mentorship and guidance to junior and mid‑level engineers, fostering a culture of excellence in data quality
• Conduct code reviews and promote engineering best practices across the data organization
• Translate complex technical concepts for non‑technical stakeholders
• Monitor and evaluate emerging technologies, tools, and methodologies in data quality, observability, and governance
• Identify opportunities for process optimization and technical debt reduction
• Lead proof‑of‑concept initiatives to validate new technologies and approaches
• Drive strategic recommendations to enhance data reliability, efficiency, and organizational data maturity

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related technical field;
  Master’s degree preferred
• 5+ years of progressive experience in data quality engineering, data governance, or data platform engineering
• Demonstrated track record of implementing enterprise‑scale data quality solutions
• Proven experience leading technical initiatives and mentoring engineering teams
• Core Technical Competencies
  • Expert‑level proficiency in SQL and query optimization techniques
  • Advanced programming skills in Python, including libraries for data processing (Pandas, Num Py, PySpark)
  • Strong understanding of distributed computing frameworks (Apache Spark, Hadoop ecosystem)
  • Deep expertise in data modeling methodologies (dimensional modeling, data vault, 3NF)
  • Comprehensive knowledge of ETL/ELT design patterns and data integration strategies
• Platform & Tools
  • Hands‑on experience with cloud platforms (AWS, Google Cloud Platform, or Azure)
  • Proficiency with modern cloud data warehouses (Amazon Redshift, Google Big Query, Snowflake)
  • Experience with data quality and observability tools (Great Expectations, Soda Core, Monte Carlo, or similar)
  • Familiarity with…