Data Governance & Metadata Engineer, Krakow, Poland

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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