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Bellese

Engineer II, Data

United States (Remote)$108.7k–$125.3kfull timemidAdded 1 month ago

About this role

Bellese is seeking a Data Engineer II to join a remote team supporting the Centers for Medicare and Medicaid Services' Hospital Quality Reporting program. You'll design and maintain backend systems, APIs, and data pipelines that help thousands of hospitals submit quality measure data while reducing provider burden and modernizing legacy systems.

What you'll do

  • Design and implement backend systems and APIs using test-driven development
  • Develop data models, ETL processes, and optimize data operations for performance and scalability
  • Contribute to automated testing suites and CI/CD pipeline implementation
  • Design user interfaces informed by UX research to meet customer needs
  • Support team members and ensure consistent feature delivery to production
  • Maintain data integrity and security across distributed computing systems

What they're looking for

  • Python and Apache Spark
  • Data modeling and ETL processes
  • API design and development
  • Distributed computing and orchestration
  • Software design patterns and algorithms
  • Agile development methodologies
  • CI/CD pipeline experience
  • Database/data warehouse querying and analysis

Benefits

  • 100% remote position
  • Opportunity to impact public health outcomes and civic healthcare
  • Work on modernizing systems serving thousands of hospitals nationwide
  • Collaborative team environment with focus on service design and UX
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Bellese

Bellese builds healthcare technology solutions focused on FHIR standards and data infrastructure to improve patient outcomes and streamline care delivery across patients, providers, and payers. The company is hiring Engineers and Data Engineers to develop backend systems, APIs, and data pipelines that modernize healthcare operations and reduce administrative burden.

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Likely interview questions

  • Walk us through a time you designed and optimized a complex ETL pipeline. What was the data volume, and how did you approach performance improvements?
  • Describe your experience with Apache Spark and Python. Have you worked with distributed computing challenges, and how did you handle them?
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