Staff Data Platform Engineer

A leading Insurtech organization made up of a few hundred experts across actuarial science, engineering, data science, and clinical practice is looking to bring on a staff level data platform engineer. Together, the team builds categorydefining, datadriven SaaS products used by insurance, health IT, and life sciences clients to make highimpact decisions at scale. As a Staff Data Engineer , you are a technical authority and multiplier. You lead through architecture, influence, and execution rather than people management. You will drive the evolution of a missioncritical data platform that must be scalable, highly secure, auditable, and performant. This role is deeply handson and centered on Databricks + AWS, with real ownership over platform direction. Requirements: 15+ years designing and building enterprise data platforms (data lakes, lakehouses, warehouses, data products) Expertlevel experience with Databricks on AWS (Delta Lake, Delta Live Tables, Unity Catalog) Proven ownership of platform architecture decisions spanning scale, performance, reliability, and cost Deep handson experience with relational and nonrelational databases (SQL Server, PostgreSQL, DynamoDB, DocumentDB or similar) Extensive experience working with healthcare and insurance data, including PHI/PII Strong working knowledge of healthcare data standards: FHIR, HL7, CCDA Experience applying clinical coding systems / ontologies: ICD10, SNOMED, LOINC, RxNorm, NDC Expertlevel data modeling for structured and unstructured data Experience building batch, streaming, and eventdriven pipelines Strong background in data governance, lineage, auditability, and security Handson experience with Infrastructure as Code (Terraform, GitHub) Proven collaboration with Data Science teams, enabling analytics and AIdriven use cases Experience in Insurtech, insurance, healthcare, or life sciences AWS Solution Architect or equivalent certification Prior ownership of platforms serving multiple external clients Data Platform Architecture Lead the design and longterm evolution of enterprise data lakes, lakehouse architectures, and warehouses Establish and enforce enterprise medallion architectures (Bronze / Silver / Gold) Make architecture tradeoffs balancing performance, cost, governance, and developer velocity Databricks & Cloud Engineering Own advanced Databricks capabilities (Delta Live Tables, Unity Catalog) Build and operate scalable, productiongrade systems on AWS Implement observability, monitoring, and cost transparency Drive Infrastructure as Code standards using Terraform and asset bundles Healthcare & Insurance Data Enablement Design pipelines for largescale healthcare and insurance datasets Implement standardsbased data models (FHIR, OMOP, HL7) Support data containing identified and deidentified PHI/PII with strict access controls Governance, Security & Compliance Implement governance frameworks for lineage, auditability, quality, and stewardship Enforce leastprivilege access and data security best practices Ensure platform compliance with healthcare and insurance regulations Pipelines, APIs & Integration Build robust ETL/ELT pipelines using SQL, Python, Scala, and Databricks tooling Design eventdriven ingestion and APIbased integrations Develop internal APIs and datasetbacked services for downstream systems Integrate with external systems (financial, HR, CRM, vendor platforms) StaffLevel Leadership Act as a thought leader and domain expert Partner across engineering, data science, analytics, product, and business teams Communicate complex technical tradeoffs clearly to senior, nontechnical stakeholders This position is open to remote work. Applicants must be willing to travel to the office in Brookfield, WI quarterly.