Director of Business Intelligence

The Public Interest Company

About The Position

Our business runs on data — client reporting, recovery performance, operational throughput, and financial results all trace back to the same underlying tables. The Director of Business Intelligence is the person who owns that picture end to end: what the data means, where it lives, whether it's right, and how it gets turned into something a business owner can act on. This is not a request-taking dashboard role. You'll build in Sigma, but the job starts before that — understanding the question behind the ask, knowing which source tables in Databricks and Postgres actually answer it, and making the call on what “correct” looks like before a single chart gets built. You'll work alongside data engineering and engineering, but you are the business owner of the data: the person who knows every table, every workflow, and every number well enough to catch it when something's off before anyone else does. Every data request in the business — from an internal ops question to client-facing reporting — should route through you, not because you gatekeep for its own sake, but because you're the only person positioned to know whether the answer is right and whether it's the right question in the first place. This is an apex individual contributor role. We're looking for someone who pairs deep technical fluency with real commercial instinct — someone who can sit with a business leader, understand what outcome they're actually chasing, and come back with an insight (not just a dashboard) that changes a decision.

Requirements

4+ years in business intelligence, analytics engineering, or a hybrid data/commercial role, with demonstrated ownership of a company's core reporting and data quality function
Strong SQL and hands-on experience with modern data warehouses (Databricks required; Postgres a strong plus)
Proven experience building and maintaining dashboards in Sigma or a comparable modern BI tool (Looker, Mode, Tableau)
Demonstrated ability to reverse-engineer and document complex, multi-source data models
Strong commercial instincts — a track record of turning data into decisions, not just reports
Experience operating as the last line of defense on data accuracy in a business with multiple workflows and complex source data
Comfortable operating as a single point of ownership across a business with no BI team beneath you — this is a builder-operator role, not a manager role (for now)
Excellent stakeholder communication; able to push back on a request and be trusted for it

Nice To Haves

Healthcare, insurance, or claims data experience a plus but not required

Responsibilities

Own the business's data graph — the map of what data exists, where it lives (Databricks, Postgres), how entities relate, and what each field actually means in practice
Serve as the single source of truth on data accuracy and data quality across the business; know the source data well enough to catch errors before they reach a dashboard or a client
Partner closely with the data engineering and engineering teams on data model design, pipeline issues, and structural changes — you don't build the pipelines, but you understand them well enough to hold the line on quality
Maintain documentation of data lineage, definitions, and known caveats so the business isn't relying on tribal knowledge
Design, build, and maintain dashboards and reporting in Sigma across all areas of the business
Own all client-facing reporting — every client data deliverable runs through you for scoping and accuracy sign-off
Act as the intake point for data and reporting requests across the business; triage, scope, and prioritize rather than simply executing what's asked
Before building anything, understand the underlying business question, the decision it will inform, and whether the requested output is actually the right one — push back and reshape the ask when it isn't
Translate data into commercial insight — not just “what happened” but “what it means and what to do about it”
Work directly with business leaders across operations, litigation, and finance to help them develop and act on insights from the data
Proactively identify patterns, risks, and opportunities in the data rather than waiting to be asked
“Sell” insights internally — present findings in a way that drives decisions and gets adopted, not just circulated
Establish and enforce a standard for data quality and validation across all reporting and dashboards
Build a process (with data engineering) to catch and resolve data discrepancies before they surface downstream
Set the standard for what “production-ready” reporting looks like at TPIC and hold that line across the business