Databricks Governance Engineer

About the role

The ideal candidate will work across cloud data platforms and enterprise data repositories to improve data quality, lineage, discoverability, and trust.

Tasks

• Identify, profile, catalog, and govern enterprise data assets across databases, cloud platforms, data lakes, and AWS S3.
• Perform data profiling, quality assessments, and reconciliation across multiple systems.
• Develop SQL queries and frameworks to identify discrepancies and validate data accuracy and integrity.
• Support metadata management, data classification, lineage, stewardship, and ownership.
• Implement automated metadata scanning, ingestion, and cataloging using Collibra and integrated platforms.
• Analyze schemas, tables, files, and pipelines to identify data quality and governance gaps.
• Collaborate with data engineers, architects, business teams, and data stewards to resolve data issues.
• Communicate findings, root causes, risks, and recommendations to technical and business stakeholders.

Requirements

• Strong expertise in data management, data governance, metadata management, data profiling, and reconciliation.
• Databricks
• Collibra or similar data governance/catalog platforms
• Strong SQL, Data Profiling & Data Reconciliation
• AWS, Amazon S3 & Cloud Data Environments
• Data Governance, Metadata Management & Data Quality
• Data Lineage, Classification & Business Glossary
• Data Analysis, Root Cause Analysis & Problem-Solving
• Preferred: Pentaho
• Preferred: AWS Glue, Athena, Redshift or Lake Formation
• Preferred: Databricks Unity Catalog and Collibra integration
• Preferred: Python / PySpark
• Preferred: Automated metadata scanning and lineage
• Preferred: Enterprise Data Lakes and Large-Scale Data Validation

How to apply

• Apply by email.

Location

• Atlanta, GA