ETL Data Engineer

7 - 10 years

20 - 25 Lacs

Posted:None| Platform: Naukri logo

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Job Type

Full Time

Job Description

ETL Data Engineer AWS & Clinical Imaging

Responsibilities

  • Design, develop, and optimize ETL pipelines for large-scale medical imaging datasets,
  • ensuring efficient data ingestion, transformation, and storage.
  • Develop scalable ETL solutions integrating with AWS (S3, Lambda, EC2, DynamoDB,
  • Redshift).
  • Design and implement event-driven workflows using Amazon EventBridge, API
  • Gateway, and AWS Lambda to automate the processing and management of medical
  • imaging data.
  • Implement PHI de-identification workflows as part of the data processing pipeline.
  • Optimize data storage and retrieval on AWS for high-performance clinical applications.
  • Integrate ETL pipelines with clinical systems using HL7 and FHIR standards.
  • Collaborate with DevOps teams for containerized and automated deployments (Docker,
  • Kubernetes, Terraform).
  • Support AI/ML teams with structured data pipelines for model training and inference.

Required Qualifications

  • 7 years (minimum) experience in data engineering with a focus on healthcare imaging
  • and medical imaging data.
  • Strong programming skills in Python, Java, and Golang for data engineering and
  • automation.
  • Expertise in medical imaging standards (preferably DICOM) and clinical metadata
  • processing.
  • Hands-on experience with AWS services (S3, Lambda, EC2, IAM, Redshift, Athena,
  • SageMaker).
  • Experience with ETL frameworks, data pipelines, and database management (SQL,
  • NoSQL, PostgreSQL, DynamoDB, etc.).
  • Familiarity with clinical metadata standards (HL7, FHIR, LOINC, SNOMED).
  • Strong problem-solving skills and ability to work cross-functionally with clinical and
  • technical teams.
  • B.E/BTech - Computer Sciences

Preferred Qualifications

  • Experience with containerized deployments (Docker, Kubernetes) for scalable
  • healthcare applications.
  • Experience with Terraform for infrastructure as code (IaC) automation.
  • Familiarity with edge computing and real-time streaming for ETL pipelines.
  • Understanding of cloud-native monitoring and logging for ETL jobs.

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