Data Quality Analyst - Databricks

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Abacus Service Corporation, is seeking the following. Apply via Dice today!The Senior Data Quality Analyst / Databricks Implementation Lead is a key technical and governance leader within the Enterprise Data Office.This role drives the strategy, design, and implementation of enterprise-wide data quality frameworks and Databricks Unity Catalog standards.The senior analyst partners with domain data owners, business data stewards, engineering teams, and platform architects to ensure data is trusted, well-governed, and consistently implemented across all domains.This position leads cross-domain onboarding into the Databricks Lakehouse, defines and enforces quality and metadata standards, and ensures Unity Catalog is used consistently as the enterprise system of record for lineage, ownership, and semantic alignment.Key ResponsibilitiesStrategic Leadership & GovernanceLead the development and enforcement of enterprise standards for Databricks Unity Catalog, Medallion architecture, metadata, and domain onboarding.Serve as a senior advisor to domain data owners and stewards on data quality, CDE definitions, and semantic alignment.Drive adoption of enterprise data governance practices across business units and technical teams.Establish and maintain enterprise data quality frameworks, KPIs, and monitoring capabilities.Databricks Unity Catalog Architecture & ImplementationDesign and oversee the implementation of domain catalogs, Bronze/Silver/Gold schemas, lineage, and metadata structures.Lead cross-domain onboarding into Unity Catalog, ensuring consistent patterns, tagging, and access controls.Partner with platform engineering to embed governance, lineage, and quality rules into Databricks pipelines.Ensure Unity Catalog is the authoritative source for ownership, sensitivity, and semantic metadata.Advanced Data Quality EngineeringArchitect and implement complex data quality rules, validation frameworks, and automated monitoring.Lead profiling, anomaly detection, and root-cause analysis for high-impact data issues.Define enterprise standards for CDE quality thresholds, rule design, and remediation workflows.Oversee quality scoring and trust indicators for Gold-layer data products.Cross-Domain Collaboration & EnablementFacilitate working sessions with stewards, owners, and engineering teams to align on definitions, lineage, and data product requirements.Mentor junior analysts and guide teams on best practices for data quality and Databricks implementation.Provide leadership in resolving cross-domain data issues, semantic conflicts, and lineage gaps.Act as the primary liaison between the Enterprise Data Office and domain teams for quality and catalog governance.Metadata, Lineage, and Catalog StewardshipEnsure all domain assets meet enterprise metadata standards before publication.Oversee the accuracy of lineage from ingestion through refined layers and data products.Maintain enterprise glossary alignment for CDEs, KPIs, and domain terms.Drive continuous improvement of catalog usability, discoverability, and trust.Required Qualifications3–10 years of experience in data quality, data governance, data engineering, or analytics.Deep hands-on experience with Databricks, Delta Lake, and Unity Catalog.Strong understanding of Medallion architecture and domain-driven data design.Expertise in data quality engineering, profiling, rule development, and monitoring.Experience leading cross-functional governance or data quality initiatives.Proficiency in SQL and familiarity with Python or PySpark.Strong communication and stakeholder management skills, including executive-level engagement.Ability to translate complex business requirements into scalable technical solutions.