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Head, Data Protection

ComplianceComplianceFull TimeRemoteLeadTeam 1,001-5,000H1B No SponsorCompany SiteLinkedIn

Location

Worldwide

Posted

88 days ago

Salary

0

Seniority

Lead

No structured requirement data.

Job Description

Head, Data Protection

Moniepoint Inc. (Formerly TeamApt Inc.)

Role Description At Moniepoint, data is the lifeblood of our financial operating system. The Head of Data Governance is a senior leadership role responsible for ensuring that this lifeblood is high-quality, secure, and accessible. You will architect and champion the enterprise-wide data governance framework, transforming how 13 million+ people’s data is managed and protected. Reporting to the Head of Enterprise Data, you aren't just a policy writer; you are a cultural catalyst. You will lead a "virtual team" of Data Stewards across the company, ensuring that while they sit within diverse units like Finance or Sales, they operate with a unified, gold-standard approach to data accountability. Qualifications - 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. - Education: A Bachelor degree in Computer Science, Engineering, Mathematics, or a related quantitative field (or equivalent practical experience). Requirements - 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. - 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. - 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. - 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. Benefits - Culture: We put our people first and prioritize the well-being of every team member. We’ve built a company where all opinions carry weight and where all voices are heard. - Learning: We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks. - Compensation: You’ll receive an attractive salary, pension, health insurance, annual bonus, plus other benefits. What Success Looks Like - Initial 6 Months: A defined Data Governance roadmap is approved, and the first "Data Health Dashboard" is live for critical data elements. - The 1-Year Mark: Every major business unit has a certified Data Steward, and automated lineage is active for our core financial products. - Culture: Data Governance is no longer viewed as a "blocker" but as the foundation that allows our product teams to build faster and safer. What to expect in the hiring process - A preliminary phone call with the recruiter - A technical panel interview with Department Leads - Technical take-home assessment - A behavioral and technical interview with a member of the Executive team - All interviews stages are Virtual

Job Requirements

  • 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.
  • Education: A Bachelor degree in Computer Science, Engineering, Mathematics, or a related quantitative field (or equivalent practical experience).
  • 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.
  • 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.
  • 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.
  • 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.

Benefits

  • Culture: We put our people first and prioritize the well-being of every team member. We’ve built a company where all opinions carry weight and where all voices are heard.
  • Learning: We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks.
  • Compensation: You’ll receive an attractive salary, pension, health insurance, annual bonus, plus other benefits.
  • What Success Looks Like
  • Initial 6 Months: A defined Data Governance roadmap is approved, and the first "Data Health Dashboard" is live for critical data elements.
  • The 1-Year Mark: Every major business unit has a certified Data Steward, and automated lineage is active for our core financial products.
  • Culture: Data Governance is no longer viewed as a "blocker" but as the foundation that allows our product teams to build faster and safer.
  • What to expect in the hiring process
  • A preliminary phone call with the recruiter
  • A technical panel interview with Department Leads
  • Technical take-home assessment
  • A behavioral and technical interview with a member of the Executive team
  • All interviews stages are Virtual

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