Staff Data Engineer

b.well Connected Health is addressing healthcare’s fragmentation problem with their FHIR-based health data management platform. They are seeking a Staff Data Engineer to design and implement robust data pipelines that support analytical and operational use cases across their platform, collaborating with various teams to enhance data-driven experiences.

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

Requirements:

• 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