Senior Data Engineer

Job Description:

We are seeking a Senior Data Engineer with expertise in medical imaging data engineering,

database ETL, and clinical imaging data to join our team. The ideal candidate will have strong

programming skills in Python, Java, and Golang, experience working with CT and MRI

metadata, and proficiency in AWS cloud services. This role will focus on building scalable data

pipelines, optimizing healthcare imaging workflows, and developing computer vision solutions

for medical imaging applications. While experience with DICOM is preferred, familiarity with

other medical imaging formats is also valuable.

Responsibilities:

Design, develop, and optimize ETL pipelines for large-scale medical imaging datasets,

ensuring efficient data ingestion, transformation, and storage.

Build and maintain medical imaging data repositories, ensuring seamless access,

query optimization, and compliance with healthcare regulations.

Implement data processing workflows for clinical imaging data (CT, MRI) to extract,

standardize, and structure metadata.

Develop scalable solutions for medical imaging data engineering, integrating with

PACS or XNAT, and other imaging systems.

Apply computer vision and machine learning techniques to analyze and process

medical images for healthcare applications, linking imaging data with associated

clinical metadata.

Extract and standardize image metadata (DICOM headers, HL7, FHIR) for enhanced

image classification and retrieval.

Develop automated image labeling and segmentation workflows using metadata

driven insights.

Collaborate with data scientists, radiologists, and software engineers to improve the

accuracy and efficiency of imaging data pipelines.

Optimize data storage and retrieval on AWS (S3, Lambda, EC2, DynamoDB, Redshift) for

high-performance clinical applications.

Design and implement event-driven workflows using Amazon EventBridge, API

Gateway, and AWS Lambdato automate the processing and management of medical

imaging data. This includes retrieving medical imaging files from imaging servers,

storing them in S3, and executing PHI de-identification before final storage.

Troubleshoot performance issues in large-scale medical imaging datasets and optimize

data infrastructure.

Required Qualifications:

7 to 10 years of experience in data engineering with a focus on healthcare imaging and

medical imaging data.

Expertise in medical imaging standards (preferably DICOM, but familiarity with other

formats is valuable) and clinical metadata processing.

Strong programming skills in Python for data engineering and automation.

Experience with ETL frameworks, data pipelines, and database management (SQL,

NoSQL, PostgreSQL, DynamoDB, etc.).

Hands-on experience with AWS services (S3, Lambda, EC2, IAM, Redshift, Athena,

SageMaker).

Background in computer vision applied to medical imaging (OpenCV, ITK, SimpleITK,

MONAI, PyTorch, TensorFlow).

Familiarity with clinical metadata standards (HL7, FHIR, LOINC, SNOMED).

Experience in optimizing high-performance storage solutions for medical images.

Strong problem-solving skills and ability to work cross-functionally with clinical and

technical teams.

Preferred Qualifications:

B.E/BTech -Computer Sciences

Experience with containerized deployments (Docker, Kubernetes) for scalable

healthcare applications.

Familiarity with edge computing and real-time streaming for medical imaging.

Understanding of AI/ML model deployment in cloud environments for medical

imaging data analysis.

Background in natural language processing (NLP) for clinical text extraction from

imaging reports.

Experience with Terraform for infrastructure as code (IaC) automation.