Data & Insight Manager

Role Purpose

The Data & Insights Manager is responsible for building and operating a data product capability that enables scalable, reliable, and actionable insights across the organisation.

This role goes beyond traditional reporting and is accountable for bridging business needs with data platform capabilities, ensuring that data is structured, governed, and delivered as reusable products.

Key Responsibilities

Data Product Ownership & Roadmap

• Define and own the data product roadmap

• Translate business needs into scalable data solutions

• Prioritise initiatives across BI, engineering, and architecture

• Ensure delivery is aligned to measurable business outcomes

Team Leadership & Operating Model

• Lead and develop a cross-functional data team (Analysts, Engineers, Architect, Scientist)

• Establish and enforce a Data-as-a-Product operating model

• Drive clarity of roles, responsibilities, and ways of working

Stakeholder Management

• Act as primary interface between data and business stakeholders

• Align Commercial, Product, Finance, Risk, Operations and Technology on data priorities

• Drive adoption of data products and insights

Data Governance & Quality

• Define and enforce data ownership and accountability

• Ensure consistency of key business metrics

• Establish data quality and trust frameworks

Delivery & Execution

• Own prioritisation and backlog management

• Ensure timely and high-quality delivery of data products

• Balance short-term reporting needs with long-term platform investments

Required Skills & Experience

• 5–10+ years experience in data, analytics, or data product roles, with at least 3+ years in a leadership or management capacity

• Proven experience owning end-to-end delivery of data initiatives, from requirements through to adoption

• Experience managing or leading cross-functional data teams (e.g. analysts, engineers)

• Strong data product mindset, with experience delivering scalable, reusable data solutions (not just reports or dashboards)

Solid understanding of:

• Data pipelines (ETL/ELT concepts)

• Data modelling (e.g. fact/dimension, semantic layers)

• Data warehousing / lakehouse concepts

• Experience working closely with Data Engineering and Architecture teams

• Strong stakeholder management skills, with the ability to influence across business and technology teams

• Ability to translate complex data into clear, actionable business insights

• Proven ability to prioritise and balance short-term delivery vs long-term platform investment

• Comfortable operating in fast-paced, evolving environments with ambiguity

Nice to Have

• Experience building or operating in a Data-as-a-Product environment

• Experience in iGaming, fintech, or other transactional platforms

• Familiarity with modern data stack tools (e.g. Snowflake, BigQuery, dbt, Airflow)

• Experience with API-driven or event-based systems

• Exposure to real-time or near real-time data processing

• Experience supporting or enabling AI/ML initiatives

• Background in both technical and business-facing roles

Success Metrics

• Adoption and usage of data products

• Improved speed and quality of decision-making

• Data consistency and trust across the organisation

• Delivery against roadmap and business impact