Founding Business Intelligence Engineer
The Public Interest Company
Founding Business Intelligence Engineer
The Public Interest Company
AI-powered healthcare third-party liability recovery
About the Company
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.
Role Overview
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, and pipeline issues.
Document analytical models, metric definitions, assumptions, and known data limitations so other teams can use and trust the data.
Establish standards for production-ready BI assets, including correctness, maintainability, performance, and documentation.
Own the BI function end to end, from understanding requirements and exploring source data to building, validating, deploying, and maintaining analytical solutions.
Prioritize BI work based on business impact, balancing immediate reporting needs with building reusable foundations.
Develop scalable reporting and self-service capabilities that reduce dependence on manual analysis and repetitive requests.
Establish practical engineering practices for BI development, including version control, testing, review, and change management where appropriate.
Work independently and make pragmatic technical decisions in a fast-moving environment with evolving requirements and imperfect data.
5+ years of hands-on experience in BI engineering, analytics engineering, data analytics, or a similarly technical role.
Advanced SQL skills, including complex joins, CTEs, window functions, query optimization, and debugging across large or complicated datasets.
Proven experience personally building and maintaining production dashboards, reporting datasets, and reusable analytical models.
Experience with modern analytical platforms such as Databricks, Snowflake, BigQuery, or Redshift, and BI tools such as Sigma, Looker, Tableau.
Strong understanding of relational data modeling, analytical transformations, metric definitions, data quality, and reconciliation.
Demonstrated ability to independently reverse-engineer unfamiliar datasets and understand relationships across multiple systems.
Experience working directly with business stakeholders to understand ambiguous requirements, investigate problems, and deliver useful analytical solutions.
Ability to connect operational metrics to business outcomes and identify insights beyond the immediate reporting request.
Comfortable being the primary hands-on BI contributor, owning implementation and ongoing maintenance without a team beneath you.
Strong attention to detail, intellectual curiosity, and a high bar for correctness.
Experience building BI or analytics capabilities from scratch in an early-stage or rapidly growing company.
Experience in operationally intensive businesses such as insurance, fintech, logistics, healthcare operations, or claims processing.
Hands-on experience with Databricks, Postgres.
Experience with dbt, Git-based workflows, automated data tests, or similar analytics engineering practices.
Experience analyzing operational funnels, productivity, unit economics, financial reconciliation, or automation performance.
Familiarity with data that changes over time, including event histories, workflow transitions, and financial outcomes that require reconciliation across systems.
Reliable BI foundation: Core business metrics are clearly defined, validated, and consistently used across internal and client-facing reporting.
Hands-on delivery: You independently build and maintain the SQL models, dashboards, and reporting tools the business needs.
Operational visibility: Business teams can understand recovery performance, case throughput, bottlenecks, and operational efficiency without relying on fragmented or manually assembled data.
Proactive problem-solving: You identify discrepancies and performance issues early, investigate their causes, and help business teams act on the findings.
Scalable analytics: Reporting becomes increasingly reusable, automated, and self-service as TPIC grows, rather than requiring more manual effort for every new question.
About the Company
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.
AI-powered healthcare third-party liability recovery
The Public Interest Company is a technology-enabled services firm that helps health plans, risk-bearing provider groups, self-funded employers, and public sector organizations recover funds that should have been paid by third-party insurers. It combines artificial intelligence, a proprietary legal-tech platform, and external data to identify and pursue third-party liability across all claim sizes, handling the entire recovery process so member care isn’t disrupted. Unlike others that rely on a single approach, the firm blends machine learning (classification, pattern mining, rules-based systems) with legal information to spot recovery opportunities that might be missed and manages the process for its clients on a fee-for-success basis. Its goal is to lower healthcare costs and improve clients’ profit margins by returning funds to fund patient care.
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