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Data Governance & Metadata Engineer

Open 54d
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.

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