Director, Business Intelligence

## Director, Business Intelligence Apply:
TG - HQ - Dallas Office:
Full time:
Posted Yesterday:
JRThe Director, Business Intelligence is the senior leader accountable for BI end to end: the quality and consistency of our data, the governance behind our metrics, how easily the business can use data on its own, and how we use analytics and AI to improve decisions and how work gets done. The Director also makes the trusted data foundation that lets every team at Topgolf use AI in its own work with confidence.

The Director leads the BI team of product owners and data engineers (~20 headcounts), partners with commercial, operations, finance, and venue leaders, and represents analytics in Technology’s planning and architecture decisions. The role reports to the VP of Finance and BI and serves the whole company, not Finance alone.# What Success Looks Like in the First 12 Months
* Executives, Finance, and venue leaders work from one set of certified metrics, and the same number appears no matter who pulls it.
* Every certified metric has a named owner, and conflicting reports and calculations are retired, with the count published
* Business users answer their routine questions without a ticket, and self-service adoption grows each quarter
* Venue leaders have a short set of operational views they trust and use during a shift.
* AI assistants answer business questions from certified metrics, respect data access rules, and have a clear process for review and correction when they are wrong.
* Develop advanced forecasting capabilities leveraging data science to improve visibility into future revenue, demand and business performance.# Team Leadership
* Lead, coach, and develop the BI team of product owners and reporting engineers; set priorities, own delivery speed and predictability, and build the next layer of leaders.
* Coach product owners in requirements gathering, backlog management, acceptance criteria, and stakeholder communication, including how to say no well.
* Set and enforce team standards for SQL, data modeling, version control, code review, testing, documentation, and dashboard design.
* Ensure a disciplined delivery cadence (intake, prioritization, release planning, and review) that balances executive requests, roadmap commitments, and technical debt.
* Set the standard for how the team uses AI in its daily work, expect every team member to use it to deliver faster and at higher quality, and require human review of what AI produces.# Data Quality & Governance
* ** Data quality and usability:
** Establish a data quality framework and own curated, well-documented models that are accurate, accessible, and easy for business users to find and use.
* ** Single source of truth:
** Make these models the authoritative source for core business metrics, require end-to-end testing of current and new metrics, and retire conflicting reports and calculations.
* ** Data and reporting governance:
** Define the process for new metrics and definitions, including ownership, approvals, calculation logic, validation, documentation, and change control.
* ** Data committee:
** Chair a small governance group that reviews and approves reporting for broad audiences, and partner with Security and Compliance on access, PII, consent, retention, and privacy requirements.
* ** AI governance:
** Make certified metrics the foundation for AI-enabled analytics so assistants and automated tools give answers the business can trust. Define what data AI tools can access, how their answers are validated, and how errors are reported and corrected.
* ** Guest 360:
** Continually connect visitation, spend, membership, segment, channel, promotions, frequency, and occasion across POS, reservations, loyalty, marketing, labor, finance, and survey…