Data Governance & Metadata Engineer
Key Responsibilities
Metadata Engineering & Automation
- Model and document data structures, metadata relationships, and end‑to‑end lineage across data platforms (including lakehouse architectures).
- Configure and maintain metadata workflows, connectors, and governance assets.
- Build automations and integrations in Java and Python (strong pandas expertise required).
- Integrate technical metadata from Databricks (Spark, Delta Lake, Unity Catalog) and Microsoft Purview into governance tools.
- Operate and troubleshoot metadata services on Linux (logs, services, deployments).
Data Governance
- Maintain data domains, dictionaries, glossaries, classification models, and stewardship structures.
- Define and enforce metadata standards and data quality rules across analytical platforms.
- Support impact analysis, remediation, and governance alignment for data products and lakehouse use cases.
Collibra / Purview
- Maintain metadata, lineage, stewardship models, and workflows in Collibra.
- Integrate Collibra with technical metadata sources (e.g. Databricks, Unity Catalog, Microsoft Purview, SQL engines) via APIs, scanners, or pipelines.
- Align governance models between Collibra and Purview (glossaries, classifications, lineage where applicable).
- Provide onboarding, training, and high‑quality documentation.
Cross‑Functional Work
- Collaborate with data engineers, platform teams, and product owners to ensure consistent governance standards in Databricks, Unity Catalog, and Purview.
- Assess risks, impacts, and compliance aspects in data‑related projects.
- Translate technical platform concepts (Spark, lakehouse, catalogs, semantic layers) into clear governance artefacts.
Required Skills
- Hands‑on experience with metadata platforms and governance tooling.
- Strong understanding of data modelling, metadata architectures, lineage, and catalog concepts.
- Proficiency in Java and Python (mandatory pandas expertise).
- Solid Linux skills.
- Experience with REST APIs, SQL, and metadata extraction.
- Practical experience with Databricks and Unity Catalog.
- Familiarity with Microsoft Purview concepts (scanning, classifications, lineage).
- Knowledge of data governance and data quality frameworks.
- Strong documentation and communication skills.
- Experience with Git and versioning workflows.
Nice to Have
- Advanced hands‑on experience with Databricks (Spark, Delta Lake, Unity Catalog, jobs).
- Experience integrating Purview and Collibra in hybrid governance setups.
- Azure services and orchestration tools experience.
- Metadata scanning, MDM, or lineage tooling experience.
- Collibra workflow development.
- Understanding of data security, classification, and access control models.
- Familiarity with industry lineage standards and open metadata approaches.
#LI-MJ1