Staff Data Engineer

 Posted 3 months ago
  
 Worldwide
  
 $155K - $180K per year
  
10+ years experience
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AI Summary

The Staff Data Engineer will design and implement robust, secure, and scalable data pipelines for analytical and operational use cases, contributing to real-time and batch data infrastructure development. This role involves integrating diverse healthcare data sources and collaborating with product, ML, and platform teams to power data-driven experiences.
Staff Data Engineer
 
This job is open to fully remote work.

About b.well

b.well is transforming the healthcare experience by empowering individuals to access and act on their complete health record. We unify data across health systems, payers, labs, pharmacies, and wearable devices using modern APIs and interoperability standards (FHIR, HL7, CCDA), helping people make better health decisions for themselves and their families.

We partner with health systems, payers, employers, and platform partners to deliver a deeply personalized and actionable health experience. Join us as we modernize one of the most complex, fragmented, and mission-critical industries in the world.

Our platform is already driving impact at scale, with integrations that include:

Walgreens – reaching over 100 million users

Samsung Health – serving more than 60 million users

Who We're Looking For

We’re hiring a Staff Data Engineer to help evolve the data and AI foundations that power personalized healthcare at scale. You will play a critical role in designing and implementing robust, secure, and scalable data pipelines that support both analytical and operational use cases across our platform.

You’ll contribute to building real-time and batch data infrastructure, integrate data from diverse healthcare sources, and collaborate closely with product, ML, and platform teams to power data-driven experiences. If you thrive at the intersection of data engineering, cloud infrastructure, and healthcare interoperability, we’d love to hear from you.

What You’ll Do
  • 8+ years of experience in software and data engineering, including 3+ years working with distributed data systems.
  • Design and implement solutions to ambiguously defined, large-scale data engineering challenges.
  • Advocate for technical excellence within the team by championing clean code, testing, and review practices.
  • Serve as a go-to technical resource, offering guidance on data systems, pipelines, and platform architecture.
  • Take initiative to enhance team capability through mentorship, pairing, and knowledge-sharing sessions.
  • Contribute to the design and scaling of event-driven and real-time data pipelines using tools like Kafka, Spark, and DuckDB.
  • Build backend services and APIs in FastAPI, MongoDB, and cloud-native environments to support product and platform needs.
  • Implement and monitor robust observability, logging, and alerting across distributed data systems.
  • Help define and improve internal development workflows, CI/CD pipelines, and deployment practices.
  • Ensure security, compliance (HIPAA, HITECH), and scalability are built into data and API solutions from day one.
What You Bring
  • Excellent problem-solving skills and the ability to work across teams and disciplines.
  • Experience designing solutions to ambiguous or high-scale data challenges across heterogeneous systems.
  • Passion for elevating team standards through best practices, automation, and repeatable workflows.
  • Strong communication skills and the ability to collaborate across engineering, product, and infrastructure teams.
  • A mentoring mindset — supporting peers through design reviews, pairing, and informal coaching.
  • Proficiency in Python and libraries like Pandas, PySpark, and FastAPI.
  • Experience with data orchestration tools such as Prefect or Airflow.
  • Familiarity with containerized environments (Docker, Kubernetes) and CI/CD workflows.
  • Understanding of healthcare interoperability standards (FHIR, HL7, CCDA) or eagerness to ramp up quickly.
Nice to Have
  • Experience deploying or supporting LLMs, ML models, or retrieval-based search systems.
  • Exposure to observability tooling (OpenTelemetry, Datadog, Prometheus).
  • Background in healthcare, healthtech, or regulated data environments.
  • Contributions to open-source projects or public repositories.
The target salary range for this position is $155,000 - $180,000 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.

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