OnMed

OnMed

Senior Data Engineer

White Plains, New York, United States · Senior

Sponsorship not specifiedDetected 22 days ago
PythonC#SQLDatabricksAzureCI/CDData EngineeringCybersecurityComplianceAuditingTest AutomationUnityHIPAAHL7/FHIREHR/EMRPublic HealthLeadershipCommunicationMentoring

About the role

  • Our path to everywhere has already begun, with our innovative CareStation, a small but mighty, Clinic-in-a-Box, bringing #healthcareaccess anywhere with an outlet to plug it in.
  • At OnMed, every role, every day, is directly impacting the communities we serve.
  • You'll join a high-performing purpose-driven team, innovating to break down the barriers that keep people from the care they need.

Responsibilities

  • You think beyond pipelines - you design resilient, scalable data platforms that power analytics, interoperability, and operational systems.
  • Role Responsibilities Enterprise Data Architecture & Platform Ownership Architect, design, and scale enterprise-grade data solutions using Databricks and Azure cloud services.
  • Own and evolve the Databricks environment, including performance optimization, cost management, governance, and security controls.
  • Integration Architecture & Interoperability Serve as lead integration architect across all system interfaces and API-driven data exchanges.
  • Design and optimize integration patterns using Azure Data Factory, Azure API Management, and event-driven architectures.
  • Data Engineering & Pipeline Development Build and optimize high-performance, scalable data pipelines in Databricks using Python and SQL.
  • Design and implement advanced data transformations and complex query optimization.
  • Implement automated testing, validation frameworks, and data quality controls to ensure pipeline reliability.
  • Drive CI/CD practices and infrastructure-as-code principles for data platform management.
  • Implement role-based access, encryption standards, and secure API management, and access controls for PHI/PII data handling.

Requirements

  • You are a senior-level Data Engineer and integration architect experienced in designing and scaling enterprise data platforms in cloud-first environments.
  • You bring deep expertise in Databricks and Microsoft Azure and have led the architecture, optimization, and governance of modern data ecosystems.
  • You are comfortable operating at both the strategic architecture level and the hands-on engineering level.
  • Deep expertise in Databricks: Delta Lake, Unity Catalog, performance tuning, cost optimization, job orchestration.
  • Advanced knowledge of Azure services including Azure Data Factory, Azure API Management, Azure Storage, and related cloud infrastructure.
  • Experience implementing event-driven or API-based integration architectures.

Nice to have

  • Knowledge, Skills & Abilities Experience operating in regulated industries
  • Strong proficiency in SQL (complex query optimization, performance tuning, indexing strategies) and Python
  • working knowledge of C# a plus.

Benefits

  • Who We Are and Why Join Us At OnMed our purpose is simple but powerful...to improve the quality of life and sense of well-being in our communities by bringing access to healthcare to everyone, everywhere.
  • This is not just a job… it's a movement to bring healthcare where and when people need it most.
  • It's healthcare that shows up.
  • You thrive in high-growth environments and are motivated by leveraging data to expand access to quality healthcare.
  • Define long-term data architecture strategy aligned to business growth and healthcare compliance, and the evolution of OnMed's CareStation and HomeStation platforms.
  • Ensure reliable, secure, and scalable interoperability between internal systems, third-party platforms, and healthcare data sources - including HL7/FHIR-based integrations with EHR and clinical systems.
  • Ensure compliance with healthcare data privacy and security regulations including HIPAA, HITRUST, and SOC 2 requirements.

This listing is sourced directly from OnMed's careers page and normalized into a canonical job model.