The Public Interest Company Logo

The Public Interest Company

Founding Business Intelligence Engineer

Reposted 2 Months Ago
Remote
Hiring Remotely in United States
Mid level
Remote
Hiring Remotely in United States
Mid level
Own the companys end-to-end data graph, ensure data quality and lineage, and deliver Sigma dashboards and client-facing reports. Act as single owner for triage, prioritization, and translation of business questions into actionable insights, partnering closely with data engineering and business leaders to set standards for production-ready reporting.
The summary above was generated by AI

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.

Responsibilities

Hands-On BI Engineering & Analytics
  • 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.

Business & Operational Analytics
  • 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.

Data Understanding, Quality & Governance
  • 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.

Foundational Ownership & Scalability
  • 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.

Qualifications

Must-Haves
  • 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.

Nice-to-Haves
  • 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.

What Success Looks Like
  • 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.

Similar Jobs

3 Minutes Ago
Remote or Hybrid
United States
125K-170K Annually
Senior level
125K-170K Annually
Senior level
Fintech • Information Technology • Insurance • Financial Services • Big Data Analytics
Leads data strategy for MetLife’s Group Benefits business by connecting business and Data & Analytics teams, establishing shared definitions, resolving ownership gaps, and improving governance and quality. The role leads Data Councils, supports Agile Release Trains, removes data-related blockers, and strengthens data foundations for decision-making, service delivery, analytics, and AI initiatives.
Top Skills: Agile Release Trains (Arts)AIAnalyticsData GovernanceData Quality
3 Minutes Ago
Remote or Hybrid
United States
42K-50K Annually
Senior level
42K-50K Annually
Senior level
Fintech • Information Technology • Insurance • Financial Services • Big Data Analytics
Performs daily accounting functions supporting incoming and outgoing funds, including wire processing, disbursements, misdirected money, suspense reconciliations, and cash reconciliations. Analyzes financial transactions, maintains general ledger accounts, investigates discrepancies, resolves reconciliation exceptions, and improves accounting processes, controls, and compliance. Partners collaboratively across teams to ensure accurate financial records and reliable customer and business fund operations.
An Hour Ago
Remote
USA
Entry level
Entry level
Insurance • Financial Services
Handle inbound cancellation calls and outbound lapse recovery to retain life insurance policyholders. Assess customer needs, recommend solutions, document interactions, meet call center KPIs, and maintain product knowledge while delivering empathetic, accurate service.
Top Skills: ExcelMicrosoft OutlookMicrosoft Word

What you need to know about the Seattle Tech Scene

Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.

Key Facts About Seattle Tech

  • Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Amazon, Microsoft, Meta, Google
  • Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
  • Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Madrona, Fuse, Tola, Maveron
  • Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account