Data Governance Engineer

Nordic Investin Group•Stockholm, ME

About The Position

Nordic Investin is recruiting a Data Governance Engineer on behalf of a partner company. The role focuses on practical data governance implemented through metadata controls and automation. The engineer will connect data catalogues, lineage and quality rules, while applying appropriate discipline to access controls, Python and SQL. The goal is to make progress that colleagues can use, leaders can evaluate and the organisation can sustain. The position involves working with product, architecture, security, operations and domain colleagues. The partner values short feedback loops, evidence from real systems and direct communication. The role calls for solid delivery experience and broader ownership, including making trade-offs visible, identifying when wider expertise is needed and moving work forward without unnecessary process. Security and operability should be considered in the design.

Requirements

  • Relevant experience delivering practical data governance implemented through metadata controls and automation in a demanding environment.
  • Strong working knowledge of data catalogues and lineage.
  • Practical experience applying quality rules and access controls.
  • Ability to assess priorities, risks and trade-offs involving Python and SQL.
  • Evidence of clear stakeholder communication and dependable end-to-end ownership.
  • Professional English and judgement to work with sensitive or business-critical information.

Nice To Haves

  • Experience from regulated enterprises and shared data platforms.
  • Exposure to governance workflows in a cross-functional or multi-team environment.
  • Swedish language skills or experience working across Nordic organisations.
  • Background in product engineering, platform work, enterprise technology or consulting.
  • Adjacent experience demonstrating transferable judgement.

Responsibilities

  • Own the practical direction for data governance implemented through metadata controls and automation.
  • Translate goals and constraints into a clear approach for data catalogues and lineage.
  • Establish useful standards, routines or decision artefacts around quality rules.
  • Coordinate stakeholders and dependencies affecting access controls.
  • Use evidence and measurable outcomes to improve Python and SQL.
  • Strengthen knowledge sharing and sustainable ownership through governance workflows.

Benefits

  • Meaningful ownership and the opportunity to influence both the solution and the decisions around it.
  • A clear mission and room to influence priorities and success measures.
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