Head of Data - Online Casino and Sportsbook

Job Title

Head of Data - Online Casino & Sportsbook

Department

Data & Analytics (Enterprise)

Role Purpose

The Head of Data is accountable for the enterprise data strategy, governance, and data platforms across the organization, encompassing customer, betting, financial, operational, HR, audit, compliance, and regulatory datasets.

The role ensures that data across all domains is accurate, trusted, compliant, auditable, and commercially valuable, while enabling data driven decision making at executive and operational levels. The role works in close partnership with Technology, Finance, HR, Compliance, Audit, and the Solutions Architect.

Key Responsibilities

• Enterprise Data Strategy & Leadership

• Define and own the enterprise data strategy covering all business domains, including:
  • Customer & betting data
  • Financial & payments data
  • Operational & contact Centre data
  • HR & people data
  • Risk, compliance, and responsible gambling data
  • Internal and external audit data
• Establish and maintain a single source of truth across the organization.
• Build and lead multi?disciplinary data teams (data engineering, BI, analytics, data science).
• Act as the executive authority for data governance, prioritization, and delivery.
• Embed a data?driven culture across the business.

• Data Architecture, Platforms & Ownership Model

• Own the data platform roadmap (not solution architecture), including:
  • Data warehousing / Lakehouse environments
  • BI, reporting, and semantic layers
  • Data quality, lineage, and observability tooling
• Define enterprise data standards, models, and structures across all domains.
• Implement a data domain ownership model, ensuring Finance, HR, Audit, Operations, and Compliance retain subject?matter ownership of their data, while adhering to enterprise standards.
• Partner with the Solutions Architect to ensure system and integration architecture supports data scalability, resilience, and compliance.

• Financial & Payments Data Responsibility

• Ensure accurate, reconciled, and auditable financial data across:
  • Deposits, withdrawals, settlements, chargebacks
  • Betting and gaming revenue (GGR, NGR, turnovers)
  • Bonus costs, promotional spend, and cost attribution
• Align operational, betting, and CRM data with Finance and General Ledger reporting.
• Support Finance with regulatory, management, and audit reporting.
• Ensure financial metrics are consistently defined and trusted across departments.

• Operational & Performance Data

• Enable data driven operational management across:
  • Call Centre and customer support performance
  • Workforce planning and productivity
  • Incident, outage, and SLA reporting
  • Retail operations (where applicable)
• Deliver operational dashboards that support real time and near real time decision making.
• Partner with Operations leaders to optimize efficiency and service quality using data.

• HR & People Data

• Establish controlled, compliant data processes for HR and people data, including:
  • Payroll, attendance, performance, recruitment, and training records
• Ensure POPIA?compliant handling, access controls, and data segregation for sensitive employee information.
• Support leadership with workforce analytics, attrition analysis, and capacity forecasting.
• Enable HR reporting without compromising privacy or governance standards.

• Audit, Risk & Compliance Data

• Ensure data structures support internal and external audit requirements, including:
  • Audit trail completeness
  • Evidence retention
  • Change and access logs
• Provide data transparency and lineage for audit review and regulatory inspections.
• Partner with Internal Audit to support issue tracking, remediation monitoring, and control testing analytics.
• Ensure regulated reporting is accurate, repeatable, and explainable.

• Responsible Gambling, AML & Risk Analytics

• Lead data driven initiatives supporting:
  • Responsible gambling detection and intervention
  • Affordability and harm prevention analytics
  • AML and suspicious transaction monitoring
  • Fraud and bonus abuse detection
• Ensure ethics, explainability, and auditability of all risk related analytics.
• Embed risk and compliance analytics into operational workflows.

• AI, Advanced Analytics & Innovation

• Own the governance and enablement of AI and advanced analytics across the enterprise.
• Support AI use cases across:
  • Customer behaviour and churn
  • Responsible gambling risk detection
  • Fraud and financial risk
  • Operational optimization
• Ensure AI models are ethical, compliant, explainable, and regulator ready.
• Stay current with emerging data and AI technologies relevant to iGaming and regulated environments.

• Data Governance, Privacy & Control Frameworks

• Define and enforce enterprise data governance, including:
  • Data ownership and stewardship
  • Data quality rules and SLAs
  • Access, masking, retention, and deletion policies
• Ensure POPIA compliance across customer, employee, and audit datasets.
• Maintain metadata, data catalogues, and lineage for transparency and auditability.

• Executive & Stakeholder Engagement

• Act as the senior data partner to:
  • Executive leadership
  • Finance, HR, Operations, Compliance, Risk, and Audit
• Translate business requirements into scalable data capabilities.
• Present insights, trends, and risks clearly to non technical stakeholders.
• Resolve cross?department data discrepancies and disputes.

Key Performance Indicators (KPIs)

• Enterprise data quality and availability
• Reconciliation accuracy between Finance, Operations, and Betting data
• Regulatory and audit outcomes
• Adoption of dashboards and self service analytics
• Responsible gambling and AML detection effectiveness
• Platform reliability and scalability
• Commercial and operational impact of data initiatives

Required Experience & Qualifications

Essential

• 8+ years’ experience in data, analytics, or BI
• 3-5 years in a senior data leadership role
• Experience in regulated, high volume transactional environments (iGaming, financial services, payments)
• Proven experience managing cross?domain enterprise data

Desirable

• Experience working with financial, HR, or audit data at enterprise scale
• Exposure to AML, RG, or fraud analytics
• Postgraduate qualification in Data Science, IT, Statistics, or related field

Skills & Competencies

• Enterprise level data governance and leadership
• Strong commercial and financial data understanding
• High regulatory and risk awareness
• Ability to balance autonomy of departments with enterprise standards
• Strong executive communication and influence
• Strategic yet hands on leadership style

Behavioral Attributes

• Ethical and accountable
• Detail oriented and data driven
• Calm under regulatory and operational pressure
• Collaborative and influence focused
• Pragmatic and outcome driven

Working Conditions

• Office-based working conditions