#Top Data Pipeline Architect

5 days ago

Allahabad, Uttar Pradesh, India beBeeDataEngineer Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Senior Data Engineer

About the Role

We are seeking a highly skilled Senior Data Engineer with deep expertise in designing, building, and operating data pipelines that support real-time clinical workflows. This is a critical role where you will create scalable pipelines that process clinical encounter data, retrieve associated medical documents, and deliver validated information to our machine learning systems for inference.

Key Responsibilities:

  • Design, build, and operate scalable, event-driven data pipelines that support real-time clinical workflows.
  • Integrate with electronic health record (EHR) systems using standards such as Fast Healthcare Interoperability Resources (FHIR) and Health Level Seven International (HL7).
  • Develop reliable systems to ingest, track, and update clinical events in real-time.
  • Ensure downstream machine learning (ML) systems receive high-quality, structured data for inference and decision support.
  • Establish observability, monitoring, and error handling for robust pipeline performance.
  • Collaborate with ML engineers to align data flows with model needs.
  • Continuously improve pipeline design to maximize scalability, resilience, and automation.

Requirements:

  • 5+ years of experience building and maintaining production-grade data pipelines.
  • Strong background in workflow orchestration and event-driven systems.
  • Proficiency with relational databases and SQL as well as handling unstructured data.
  • Experience operating in cloud environments and working with distributed, highly available systems.
  • Track record of delivering data infrastructure that supports ML or analytics applications.
  • Excellent communication and collaboration skills.

Bonus:

  • Knowledge of Health Insurance Portability and Accountability Act (HIPAA) and healthcare data security/privacy requirements.
  • Familiarity with FHIR/HL7 data modeling in production settings.
  • Experience supporting ML inference pipelines in real-world applications.
  • Expertise with image data.
  • Exposure to vector databases, embedding stores, or document retrieval systems.

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