Director, Business Intelligence

About the Role

Enterprise Operations exists to ensure Take Command can scale efficiently and reliably by owning the internal systems, data, execution, and partnerships that power the business. We design, operate, and continuously improve the company’s internal operating model so teams can move faster, make better decisions, and scale with confidence.

We’re hiring a Director of Data & Business Intelligence to be a foundational leader within Enterprise Ops — someone who can build the data and BI muscle the company needs today while shaping how data, automation, and insight support scale over time.

This role is both hands-on and strategic. You’ll start by building core BI assets yourself, alongside a small team, and evolve into a leader who defines how data is governed, interpreted, and used across Operations, Finance, Product, and Go-To-Market teams. You’ll also play a key role in identifying opportunities to reduce manual work through automation and applied AI.

What You’ll Do

• Own the company’s business intelligence strategy, including KPIs, dashboards, and executive reporting

• Build and maintain core BI assets hands-on early (models, dashboards, metric definitions)

• Establish clear, lightweight data governance: definitions, documentation, and change management

• Partner closely with Engineering to ensure reliable, well-understood data flows without owning core platform infrastructure

• Design how insights are delivered so they drive action, not just visibility

• Identify opportunities to automate manual reporting, reconciliation, and operational workflows, including the thoughtful use of AI where it adds leverage

• Act as a strategic thought partner to leadership on performance, growth, and operational efficiency

• Gradually build and lead a small, high-impact data team

What You’ll Own

• Company KPIs and executive reporting

• Standard dashboards used across Operations, Finance, Support, and GTM

• Metric definitions and the data dictionary

• The BI and analytics layer (e.g., Looker, semantic models, reporting tools)

• Governance processes for introducing or changing metrics

• Identification and prioritization of automation and AI opportunities within data and reporting workflows

How You’ll Work (Enterprise Ops Principles in Practice)

• Build things that help everyone: You design data systems and reporting that scale beyond yourself and make the whole company better

• Seek clarity over comfort: You notice when numbers don’t line up, reduce ambiguity, and push toward clear decisions

• Own the outcome: You step in and move things forward, even when ownership or the path isn’t obvious

• Be technically grounded and customer-true: You understand the data, systems, and domain deeply and use that judgment to do right by the business and customers

• Stay curious and open-minded: You explore new approaches (including AI and automation), invite correction, and keep improving without losing attention to detail

Who You Are

• 8–12+ years experience in data, analytics, BI, or related fields

• Experience building or rebuilding a BI function in a growing company

• Comfortable operating as a player-coach — strategic, but willing to get into the weeds

• Strong business intuition; you understand how operational, financial, and go-to-market metrics fit together

• Confident influencing senior stakeholders and navigating ambiguity

• Pragmatic and execution-oriented — you know when “good enough” unlocks momentum

Nice to have

• Experience reducing manual operational work through automation or AI

• Background in fintech, healthcare, benefits, or other regulated environments

• Experience with modern BI stacks and semantic layers

What Success Looks Like

• Leadership trusts and uses a consistent set of metrics to run the business

• Teams spend less time reconciling numbers and more time acting

• Manual reporting and operational overhead decrease through automation

• BI is seen as a strategic partner within Enterprise Ops, not a reporting queue

• The data foundation is strong enough to scale without rework

Compensation: $158,000-$178,000 + 15% bonus

First 3 Months Deliverables

Month 1 — Clarity, Baseline, and Leverage Points

• Agreed-upon list of core company KPIs

• Documented definitions for the highest-impact metrics

• Inventory of existing dashboards, reports, pipelines, and manual data processes

• Identified 2–3 priority data or reporting issues to address first

• Identified top manual workflows (reporting, reconciliation, ops support) suitable for automation

• Initial draft of a data dictionary

Signal: understands the business, the data, and where automation will matter.

Month 2 — Standardization, Early Wins, and Automation Pilots

• Standardized definitions for core operational, financial, and GTM metrics

• 1–2 improved or newly standardized dashboards in active use

• Reduction or consolidation of duplicate/conflicting reports

• Published v1 data dictionary with named owners

• At least one manual workflow reduced or automated (reporting, reconciliation, or data QA)

• Defined lightweight process for requesting or changing metrics/reporting

Signal: delivers visible value and starts reducing operational drag.

Month 3 — Trust, Operating Model, and Scale Readiness

• Finalized core KPI set actively used by leadership

• Executive reporting that ties together Ops, Finance, and GTM performance

• Established data governance rhythm (cadence, approvers, documentation)

• Clear roadmap for:

  • BI improvements

  • Data quality enhancements

  • Further automation and applied AI opportunities

• Defined team operating model (roles, responsibilities, near-term hiring)

Signal: the foundation is solid, trusted, and ready to scale.