Manager, Analytics Engineering

TKO

About The Position

Who We Are: TKO Group Holdings, Inc. (NYSE: TKO) is a premium sports and entertainment company. TKO owns iconic properties including UFC, the world’s premier mixed martial arts organization; WWE, the global leader in sports entertainment; and PBR, the world’s premier bull riding organization. Together, these properties reach 1 billion households across 210 countries and territories and organize more than 500 live events year-round, attracting more than three million fans. TKO also services and partners with major sports rights holders through IMG, an industry-leading global sports marketing agency; and On Location, a global leader in premium experiential hospitality. The Role The Manager, Analytics Engineering sits within Data & AI Product and Services and leads the enterprise reporting and analytics engineering function. This role is responsible for building, standardising, and scaling trusted reporting products across TKO’s global brands. You will lead a team of BI / analytics engineers responsible for semantic models, metric definitions, dashboards, data visualisation standards, and reporting automation. The role will partner closely with Data & AI Product Management, Data Engineering, Data Science, Data Governance, and business stakeholders to ensure reporting assets are accurate, scalable, governed, and aligned to enterprise data domains. This role bridges business insight needs with modern data platform capabilities.

Requirements

7+ years in analytics engineering, BI engineering, or advanced reporting roles.
2+ years leading or mentoring analytics / BI engineers.
Strong experience with modern data stacks (e.g., Snowflake, dbt, BI platforms).
Deep understanding of dimensional modelling and semantic layer design.
Experience defining enterprise KPI frameworks and governance controls.
Strong SQL and data transformation skills.
Familiarity with CI/CD, version control, and analytics engineering workflows.
Experience working in federated, multi-brand organisations.
Strong stakeholder communication skills, including executive reporting exposure.

Nice To Haves

Experience supporting executive and board-level reporting.
Familiarity with data cataloguing and lineage tooling.
Experience with self-service analytics enablement.
Exposure to AI-driven insights or automated reporting.
Experience working in sports, media, entertainment, or large event-driven businesses.

Responsibilities

Reporting & Analytics Engineering Leadership Lead and develop a high-performing team of BI and analytics engineers. Own the enterprise reporting engineering roadmap in partnership with Data Product management. Establish scalable patterns for dashboard development, metric definition, and semantic modelling. Standardise enterprise KPI definitions and reporting frameworks across brands. Ensure consistent data modelling approaches aligned to canonical domains.
Data Modelling & Semantic Layer Ownership Design and maintain curated, analytics-ready data models. Own semantic layers, business logic, metric libraries, and reporting data marts. Partner with Data Engineering to optimise transformations and pipelines. Implement testing, version control, CI/CD, and observability for reporting assets. Ensure lineage and metadata are properly documented in the enterprise catalog.
Governance & Quality Embed data quality checks and validation frameworks into reporting workflows. Ensure alignment with data governance standards, access controls, and privacy requirements. Eliminate duplicate or shadow reporting solutions across the organisation. Drive certification processes for enterprise dashboards and KPIs. Support auditability and traceability of business metrics.
Product & Stakeholder Partnership Translate business insight needs into scalable reporting solutions. Partner with Product Managers to prioritise reporting backlogs. Support executive dashboards and board-level reporting frameworks. Promote self-service analytics capabilities through enablement and training. Establish SLAs for reporting delivery and support.
Operational Excellence Implement development standards, code review processes, and release governance. Drive performance optimisation and cost efficiency of reporting workloads. Maintain documentation, onboarding materials, and reporting playbooks. Manage vendor tools and BI platform administration where applicable. Continuously improve reporting maturity across brands.
Behavioural Competencies Strategic Execution – Connects reporting outputs to business outcomes and enterprise data strategy. Ownership & Accountability – Takes responsibility for data accuracy, reliability, and scalability. Collaboration – Works effectively across Product, Engineering, Governance, and business teams. Data Stewardship Mindset – Treats metrics and models as enterprise assets. Continuous Improvement – Drives automation, standardisation, and engineering best practices. Influence Without Authority – Aligns federated business teams to enterprise standards.

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