Nym
Nym
Nym develops healthcare software that automates medical coding within the revenue cycle management process. Its autonomous coding engine interprets clinical language in patient charts and assigns medical charge codes in seconds, helping healthcare providers improve coding consistency while reducing the time and administrative cost involved in coding. By handling this work automatically, Nym enables clinical and administrative teams to devote more attention to patient care.

Software Engineer, Data Platform

Build AWS data pipelines and platform infrastructure for Nym’s healthcare coding engine. Strengthen delivery, observability, reliability, and security for systems handling patient data.

Description

  • Develop dependable pipelines to process healthcare data at scale, covering millions of charts annually.
  • Build and run AWS cloud infrastructure managed through code.
  • Lead data modeling, schema management, and database performance work with the DBA.
  • Improve software delivery with CI/CD, environments, observability, and internal tools.
  • Use AI coding assistants in daily work and apply LLMs and agent-based tools to automate data and platform tasks.
  • Protect the security, reliability, and compliance of systems that handle sensitive patient information.
  • Work with R&D, ML, and Product to turn requirements into scalable data and platform solutions.

Requirements

  • Bring at least five years of professional software engineering experience, including substantial backend, data, or platform work.
  • Demonstrate strong Python skills.
  • Have proven experience building and operating data engineering systems, including batch or streaming pipelines, ETL/ELT, and workflow orchestration.
  • Be proficient in SQL and relational databases such as PostgreSQL, including data modeling and query optimization.
  • Bring practical experience with AWS.
  • Have experience building and maintaining CI/CD pipelines.
  • Use AI development tools such as Claude Code, Cursor, or Copilot effectively, and know when their output requires human review.
  • Communicate clearly and work well with colleagues across functions.
  • Be comfortable working across time zones in a global, fast-growing, dynamic environment where requirements may be ambiguous.
  • Be fluent in written and spoken English.

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