Staff Engineer, Healthcare Data at b.well Connected Health

, , -

Full Time

Start Date

Immediate

Expiry Date

14 Oct, 26

Salary

220000.0

Posted On

16 Jul, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Apache Spark, PySpark, Databricks, Delta Lake, Python, SQL, HL7 FHIR R4, US Core, USCDI, HL7 v2.x, C-CDA, SNOMED CT, LOINC, RxNorm, ICD-10, HIPAA

Industry

Hospitals and Health Care

Description

Staff Engineer, Healthcare Data Individual Contributor — Staff Level Health Data Platform · FHIR at Scale Company Overview b.well is solving healthcare's fragmentation problem with our FHIR-based health data management platform. The platform connects data from EHRs, wearables, portals, and other sources, while our intelligence engine personalizes the consumer experience. By simplifying the complex healthcare ecosystem, we make it easy and convenient for consumers to engage and take action—whether it's scheduling care, setting reminders, accessing health data, and more. For our clients, this means better health outcomes, operational efficiency, and stronger consumer engagement. The Role You'll set the technical direction for how b.well ingests, transforms, and delivers healthcare data at scale on our FHIR-based platform—owning our hardest problems (large-scale pipeline performance, data quality and de-duplication, terminology normalization, and reliable delivery of standards-conformant FHIR) and turning each solution into reusable frameworks the whole team builds on. This is an AI-native role: you'll pair first-principles engineering rigor with modern agentic tooling—coding agents such as Claude Code and reusable AI skills—to ship faster and turn raw health data into trustworthy, reasoning-ready health data intelligence. What You'll Do: Work AI-Native & Set the Bar * Make coding agents (e.g., Claude Code) and reusable AI skills a first-class part of how the team engineers—shipping faster by automating the repetitive and amplifying the hard parts * Bring the rigor to know when to trust an agent, when a deterministic rule-based approach wins, and how to keep AI-generated code correct, tested, and PHI-safe * Package engineering and data-quality judgment into reusable tooling the whole team applies consistently Build & Scale Healthcare Data Solutions * Own the end-to-end architecture of large-scale pipelines that transform raw source data into clean, standards-conformant FHIR * Diagnose and eliminate performance and scaling bottlenecks in distributed processing so jobs run faster and more cost-efficiently * Set standards for data quality, de-duplication, patient/record linking, and terminology normalization; drive reliable, idempotent delivery at production volume * Build automated testing and validation for data quality and FHIR conformance Lead, Secure & Mentor * Set technical direction across ingestion, transformation, and delivery, and define the frameworks and standards that accelerate the team * Champion PHI-safe engineering and uphold HIPAA, 21st Century Cures Act, and ONC/CMS compliance across the platform * Mentor senior and mid-level engineers, and represent b.well in relevant standards and industry discussions Required Experience: Must-Have * 8+ years in data engineering, health IT, or healthcare interoperability—with a Staff-level track record of owning systems, not just tasks * Proven production experience building large-scale health-data pipelines and owning a complex platform end-to-end, including its hardest performance and correctness problems * Experience defining frameworks and standards that measurably accelerated a team * AI-native engineer: you already ship with coding agents (e.g., Claude Code) and reusable AI skills, and can raise the whole team's leverage without compromising engineering rigor Technical Skills * Distributed data engineering: Apache Spark / PySpark at scale (partitioning, performance and memory tuning); lakehouse tooling such as Databricks and Delta Lake; schema evolution; batch and streaming pipelines * Pipelines & languages: ETL/ELT, CDC, incremental/delta and idempotent processing; strong Python (required) and SQL; Git, CI/CD, and automated testing * FHIR & standards: HL7 FHIR R4 (resources, profiles, Bundles), US Core / USCDI, and HL7 v2.x / C-CDA to FHIR conversion * Terminologies & payer data: SNOMED CT, LOINC, RxNorm, ICD-10, CPT, CVX and crosswalks; claims, coverage, and eligibility data models * Compliance: HIPAA, 21st Century Cures Act, ONC certification, and CMS Interoperability Rule Preferred * Large-scale FHIR data modeling; patient matching / MPI and clinical data-quality profiling * Payer data exchange (CARIN Blue Button, Da Vinci) and lab/pharmacy data * LLMs/agents for clinical data extraction, normalization, and terminology mapping; open-source healthcare or HL7 working-group contributions What Makes You Successful: * Deep curiosity and passion for hard healthcare-data problems, with relentless debugging instincts across multi-stage pipelines * Uncompromising commitment to data quality, patient safety, and PHI/consent security * Self-directed—you drive ambiguous problems to a production fix and communicate clearly to technical and non-technical audiences * AI-native by default: fluent with coding agents (e.g., Claude Code) and reusable AI skills, shipping faster without sacrificing rigor * Strong engineering mindset: first-principles thinking, deep ownership, correctness over cleverness * Treats health data as intelligence: turns messy source data into clean, coded, de-duplicated, reasoning-ready records The target salary range for this position is $180,000 - $220,000 annually and is part of a competitive total rewards package including stock options, benefits, and incentive pay for eligible roles. Individual pay may vary from the target range and is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. We review all employee pay and compensation programs annually at minimum to ensure competitive and fair pay. Data shows that women, people of color, and other underrepresented groups may be less likely to apply for jobs unless they believe they are a perfect match. But b.well holds diversity amongst its key values, and we have a strong commitment to building our workforce and products through that lens. You don't have to check every box in this job description to be a great fit for the role! If you're excited about this position and the prospect of working for b.well, please apply. If it turns out this role isn't for you, there may be other openings that could align with your experience and expertise! We are committed to an inclusive and diverse b.well. We are an equal opportunity employer. We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, age, disability, veteran, genetic information, marital status or any other legally protected status

Responsibilities

Set the technical direction for ingesting, transforming, and delivering healthcare data at scale on a FHIR-based platform. Lead the implementation of AI-native engineering practices and mentor senior and mid-level engineers.