Moniepoint Incorporated

Finance & FinTech

Head, Data Governance

Job details

Contract Type

Description
  • Experience: 9+ years of leadership experience in Data Governance, Data Engineering, or Data Strategy within a high-growth environment.

  • Technical Proficiency: Advanced SQL and Python skills are essential. You should be comfortable auditing a data platform directly and working with APIs for automation.

  • Framework Expertise: Deep knowledge of modern data architectures (Data Mesh, Data Vault 2.0) and how to apply governance within them.

  • Regulatory Knowledge: Intimate familiarity with NDPR, GDPR, and fintech-specific data regulations.


Responsibilities
  • 1. Strategic Leadership & Framework Design

  • Governance Roadmap: Develop and execute a long-term strategy that aligns with Moniepoint’s mission to build the financial OS for emerging markets.

  • Policy & Standards: Author and maintain global policies (Privacy, Retention, Naming Conventions) that are clear, actionable, and "Regular Guy" friendly.

  • Operating Model: Define our domain-driven structure and clarify data ownership across the company to eliminate ambiguity.

  • 2. Functional Leadership of the Stewardship Team

  • Orchestration: Direct the strategic priorities of Business Unit Data Stewards, ensuring they have the tools and training to succeed.

  • Community Building: Create a "Data Governance Academy" to onboard, certify, and mentor stewards across the organization.

  • KPI Alignment: Set the functional goals that define what "good" looks like for data quality within each business unit.

  • 3. Tech Stack & Automation Ownership

  • Platform Strategy: Select and manage our governance platforms (e.g., Atlan, Collibra, or Microsoft Purview), ensuring they integrate seamlessly with our data lake.

  • Metamodel Design: Configure tools to link business terms to physical technical assets, creating a transparent data lineage.

  • Governance-as-Code: Partner with Data Engineering to automate quality checks and PII masking within the CI/CD pipeline.

  • 4. Risk, Compliance & Culture

  • Enterprise DQ Reporting: Build "Data Health Dashboards" for the Executive team to provide visibility into our data reliability.

  • Change Management: Lead the cultural shift from "data is IT’s problem" to "data is a strategic business asset."

  • Literacy Programs: Develop workshops to empower non-technical staff to read, interpret, and respect data.


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