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Job Description

Join a fast-paced product platform team at Robotics Technologies in New York, NY (onsite). This Senior Data Engineering role focuses on building a modern, scalable healthcare enrollment data platform powered by Databricks. You will have the immediate opportunity to deliver X12 EDI 837/835 processing capabilities, while working on high-volume, production-grade data pipelines that support enrollment, eligibility, and claims-related workflows.

What you will build and improve

  • Design, develop, and maintain scalable data pipelines using Databricks
  • Develop and support X12 EDI processing, with emphasis on 837, 835, and 834 transactions
  • Create high-volume, production-grade data engineering solutions for healthcare enrollment and related data
  • Work with Delta Lake, Apache Spark, Databricks Notebooks, and Databricks Pipelines
  • Process and transform healthcare enrollment, eligibility, and claims-related data

Security and operational ownership

  • Ensure data security and compliance with HIPAA, including appropriate handling of PII and PHI
  • Troubleshoot, optimize, and maintain existing data pipelines
  • Work independently in a fast-paced program environment

What you bring

  • 6+ years of experience in Data Engineering
  • Strong hands-on experience with Databricks including Delta Lake, Spark, Notebooks, and Pipelines
  • Strong working knowledge of X12 EDI standards, specifically 837, 835, and 834
  • Proficiency in Python and PySpark
  • Experience building and maintaining high-volume, production-grade data pipelines
  • Healthcare domain experience, including knowledge of PII, PHI, and HIPAA compliance
  • Familiarity with healthcare enrollment and eligibility data workflows
  • Ability to work independently and deliver in a fast-paced environment

Good to have

  • Previous experience with healthcare clearinghouse integrations
  • Experience with healthcare EDI transaction processing and integrations

Technologies: Databricks, PySpark, Python, X12 EDI, Delta Lake, Apache Spark, Databricks Notebooks, Databricks Pipelines

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