Founding Business Intelligence Engineer

The Public Interest Company provides a comprehensive solution for identifying and recovering third party liability for health plans, risk-bearing provider groups, and self-funded employers. We combine AI and a legal tech platform to identify and recover claims that should have been paid by third party payers. We handle the entire recovery process, all while protecting members and streamlining operations. We empower healthcare organizations to maximize their financial performance and recoup dollars towards care delivery, without adding administrative burden.

Our business runs on data. Recovery performance, operational throughput, client reporting, and financial results are deeply interconnected, and we need someone who can turn that complexity into reliable, actionable information.

We're looking for a founding, hands-on BI engineer to build and own TPIC's business intelligence foundation. You'll work directly with raw data in Databricks and Postgres, develop analytical models, write complex SQL, build dashboards and reporting, and establish the definitions and quality standards that make our data trustworthy.

This is not a request-taking dashboard role, nor is it a position where you manage others to do the technical work. You'll personally build the tools and analytical foundations the business depends on, while developing a deep understanding of how our operational workflows translate into recovery and financial outcomes.

The right person combines strong technical execution with curiosity and business judgment. You'll work directly with operations, finance, litigation, and engineering to understand the question behind a request, investigate discrepancies, and identify insights that improve business performance. You should be comfortable working independently in an environment where data is imperfect, requirements are ambiguous, and the right solution often needs to be discovered rather than specified.

This is a founding individual contributor role with end-to-end ownership of BI. You'll establish the technical and analytical foundation that scales as TPIC grows.

• Design, build, and maintain dashboards, reports, and analytical tools used across operations, finance, litigation, and client-facing workflows.

• Write and optimize complex SQL to analyze large datasets, reconcile data across systems, and solve ambiguous business questions.

• Build and maintain reusable analytical data models, transformations, and metric definitions on top of data in Databricks, Postgres, and other source systems.

• Develop reliable reporting datasets and semantic definitions that support consistent metrics across dashboards, analysis, and client deliverables.

• Independently investigate data discrepancies, trace issues to underlying sources, and work with engineering to resolve root causes.

• Improve the performance, reliability, and maintainability of BI queries, models, and reporting workflows.

• Develop a deep understanding of TPIC's recovery lifecycle, from incident identification and validation through pursuit, recovery, and financial reconciliation.

• Build analytics that track recovery performance, case throughput, processing efficiency, operational bottlenecks, and unit economics.

• Partner with business stakeholders to understand operational questions, translate them into analytical requirements, and deliver solutions that enable better decisions.

• Proactively investigate performance changes, identify root causes, and surface opportunities to improve recovery outcomes and operational efficiency.

• Develop measurement frameworks for operational changes and automation initiatives, helping teams determine whether improvements are delivering the expected impact.

• Go beyond presenting metrics to explain what they mean, why they changed, and where the business should investigate or act.

• Build and maintain a comprehensive understanding of the business's analytical data landscape, including source tables, entity relationships, workflow states, and data lineage.

• Establish and maintain consistent definitions for business-critical metrics across operational, financial, and client reporting.

• Implement validation checks, reconciliation logic, and quality controls to detect missing, inconsistent, or inaccurate data.

• Partner closely with data engineering and software engineering on source data quality, schema changes, data modeling,…