Data Governance Expert

~220 - 240 PLN/ godz./ godz.B2BB2B (netto)

C-Level / ManagerZdalnie·WarszawaFull-time·B2B

#479525·Dodano 2 dni temu·2

Źródło: justjoin.it

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Tech Stack / Keywords

DAMA CDMPEDM Council DCAMData Mesh ArchitectureDatabricksUnity CatalogAccess Control ModelsData Lineage ToolsAPI / Data Sharing Contracts

Podsumowanie oferty

Design and implement a federated data governance framework within a Data Mesh architecture, initially onboarding the Logistics domain. Partner with Data Engineering and Platform teams to implement governance capabilities using Databricks and Unity Catalog.

Wymagania

5+ years of progressive experience in Data Governance, Data Management, or Enterprise Data Architecture within a global or complex multinational organization.
Solid experience establishing governance frameworks within a Data Mesh or decentralized data architecture.
Proven experience defining data contracts, interoperability standards, and enterprise business glossaries.
Experience with sustainability reporting data (e.g. EPDs, carbon accounting) or supply chain/logistics data.
Hands-on experience or deep technical understanding of the Databricks platform, particularly Unity Catalog, access control models, and data lineage.
Strong knowledge of data lifecycle management, data privacy, data security principles, and enterprise data cataloging tools.
Demonstrated understanding of Data-as-a-Product concepts, API/data sharing contracts, and domain-driven design.
Proven ability to influence and align diverse business and technical stakeholders across different geographical regions and business units.
Excellent verbal and written communication skills, with the ability to translate complex technical governance topics into business value.
Consultative mindset and ability to challenge decisions while proposing safer alternatives.
Good command of English.

Nice to have:

Certifications such as DAMA CDMP or EDM Council DCAM are an advantage.

Obowiązki

Design and implement a federated data governance framework within a Data Mesh architecture.
Lead governance onboarding for new business domains, initially focusing on Logistics and building on existing practices in the EPD and Sustainability domain.
Develop reusable governance onboarding blueprints for future domains.
Define enterprise standards and policies covering the full Data Product lifecycle.
Define ownership models, SLAs, metadata requirements, data quality metrics, and governance expectations for Data Products.
Define and support data contracts, interoperability standards, and enterprise business glossaries.
Partner with Data Engineering and Platform teams to implement governance capabilities directly within Databricks.
Support governance through Unity Catalog, automated policy enforcement, access control models, auditing, and data lineage.
Drive the adoption of enterprise data cataloging, metadata management, lineage tracking, and data discovery practices.
Coach domain leaders, Data Product Owners, and Data Stewards in defining and maintaining data quality controls and operational SLAs.
Establish KPIs for data quality, platform adoption, catalog completeness, and regulatory or policy compliance.
Ensure Data Products comply with applicable global data protection requirements, internal security policies, and relevant sustainability reporting standards.
Support governance requirements related to standards and regulations such as CSRD and EPD regulations, where applicable.
Act as a governance champion and key alignment point between business domains, Platform Engineering, Analytics teams, and executive stakeholders.
Develop governance playbooks and conduct workshops to build governance capabilities within domain teams.
Promote a Data-as-a-Product culture throughout the organization.
Collaborate with stakeholders across Marketing & Innovation, Finance, Sustainability, Compliance, Legal, Security, Investor Relations, and Public Affairs, as well as third-party vendors.

Inne informacje

Work from the European Union region and a valid work permit are required.
Recruitment process: CV review, HR call, interview, client interview, and decision.

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