Note: The job is a remote job and is open to candidates in USA. b.well Connected Health is solving healthcare’s fragmentation problem with their FHIR-based health data management platform. They are seeking a Staff Data Engineer to design and implement robust, secure, and scalable data pipelines that support both analytical and operational use cases across their platform.
Responsibilities
- 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
Skills
- 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
- 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
- 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
Benefits
- Stock options
- Benefits
- Incentive pay for eligible roles
Company Overview