Data Product Manager and Governance Lead

Job Description

We are looking for a Data Product Manager and Governance Lead to bring structure, alignment, and momentum to how QIMA defines, governs, and leverages its data assets. This is a high-impact, cross-functional role with a dual mandate:
Solidify and own the data foundations QIMA needs across systems and business units, and translate those foundations into high-value initiatives that improve operations, analytics, AI readiness, and client-facing data products.

You will orchestrate the definition of shared data ontologies, map data lineage, and drive the adoption of master data practices across systems and business units. Working hand-in-hand with business experts, data owners, system owners, and the data team, you will ensure that data definitions are unified, data contracts are implemented, and the right foundations are in place to power reliable analytics, seamless cross-system consolidation, and data products that create measurable value, both internally and for QIMA's clients.

If you thrive on leading through influence across cultures and geographies, turning complexity into a clear roadmap, and shipping data initiatives that unlock both operational efficiency and commercial opportunity, we’d love to hear from you.

• Master Data Management
  :
  Define and maintain shared ontologies, taxonomies, code lists, and reference data across QIMA's systems. Ensure every critical entity has a single authoritative definition and a governed master record, and drive convergence where today each system has its own fields and definitions. Maintain the broader documentation practice (data dictionary, data product specs, onboarding guides, and change logs) so that standards are findable and usable.
• Governance Design
  :
  Design the accountability framework that makes governance stick: clarify Data Owner responsibilities by domain, align System Owners, establish how conflicting definitions get resolved across BUs. Translate ownership into practice through data contracts and end-to-end lineage coverage. Select and drive adoption of governance tooling (data catalogue, lineage, contract management).
• Stakeholder Adoption
  :
  Act as the central coordination point across business experts, Data Owners, and engineering — gathering requirements, translating them into specifications, driving validation, and tracking adoption. Ensure all parties have the playbooks and documentation they need to work from shared standards. Shift mindsets from "my system, my definitions" to a company-wide approach.
• Impact Analysis
  :
  Partner with data engineering and architecture teams to create and maintain end-to-end data lineage across source systems, integration layers, and reporting. Assess and communicate the downstream impact of any data model change, system evolution, or new integration before it ships. Ensure changes are coordinated, not discovered after the fact.
• Prioritization & Roadmap
  :
  Own the data governance roadmap. Decide what gets standardized first, which ontology or master data initiative takes priority, and how efforts are sequenced across systems and business units. Balance quick wins with structural improvements. Manage timelines, dependencies, and delivery milestones.
• Data Collection by Design
  :
  Partner with product teams to ensure new features and system workflows are designed to capture data correctly at the source — right structure, right granularity, right moment. Challenge design decisions (free text vs. controlled list, optional vs. required, field naming) before they ship. Prevent the downstream consolidation problems that come from poor upstream collection choices.
• Strategic Data Initiatives
  :
  Identify, prioritize, and drive high-value data initiatives that build on QIMA’s governed data foundation. Partner with business, product, commercial, and operations teams to translate improved data assets into measurable outcomes, such as improved customer/account views, operational performance insights, risk and quality intelligence, automation opportunities, and client-facing data products. Ensure governance work is tied to real use cases and business value, not just treated as a standalone compliance…