Data Quality Analytics Engineer - W2 (No C2C or 1099) - Hybrid in Irving, TX or Miami, FL (Posted SAM)

Required:

• 5–7 years of experience in analytics, data engineering, data quality, or data management, including hands-on delivery on analytics projects and exposure to data quality, master data management, and/or data protection initiatives
• Strong proficiency in SQL and Python for data analysis, quality rule development, and reconciliation across relational and cloud-native platforms
• A genuine proponent of data quality and data trust practices - someone who argues for the right fix rather than the fast one, and can explain why it matters to a non-technical audience
• Working knowledge of core data quality concepts: profiling, rule authoring, exception management, reconciliation, and quality metrics
• Understanding of master data management fundamentals - matching, survivorship, golden records, and hierarchy management
• Awareness of data protection concepts: sensitive data classification, masking, least-privilege access, and the regulatory drivers behind them
• Demonstrated ability to turn data into analytics people act on - dashboards, scorecards, or reporting products with a real audience
• Solid understanding of data governance principles, data cataloging, metadata management, and data lineage
• Experience defining data quality metrics and SLAs and reporting on data health to senior stakeholders
• Ability to work collaboratively with business users, data stewards, and technical teams to gather requirements and deliver solutions
• Strong adherence to software engineering best practices including version control (git), modular code design, Agile methodologies, and CI/CD pipelines
• Curiosity and speed in learning emerging data quality and AI technologies, and comfort adapting to an evolving enterprise data landscape
• Bachelor’s degree in Computer Science, Information Systems, Data Science, or a related field; equivalent practical experience will be considered