Data Engineer - Python | PySpark | ETL/ELT

Key areas of responsibility
Design and develop cloud-native backend microservices that collect data from medical systems, hospital information systems, radiology information systems, and PACS.
Build ingestion pipelines for healthcare and imaging data, including DICOM and HL7 formats.
Extend platform data-collection frameworks to support recent data sources, integrations, and cloud-based workflows.
Develop reliable, scalable, and fault-tolerant data-transport services with appropriate retry, error-handling, monitoring, and dead-letter mechanisms.
Collaborate with data engineers to ensure ingested data meets defined schema, integrity, and quality standards.
Package and deploy services using containers and Kubernetes.
Contribute to automated build, testing, deployment, and CI/CD processes.
Work with technical leaders and system engineers to align integration solutions with the wider platform architecture.
Ensure services comply with cybersecurity, data-privacy, and regulatory requirements for healthcare and medical-device software.
Develop unit, integration, and end-to-end tests and maintain transparent documentation for APIs, data flows, and deployment configurations. Work Experience





Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field. 69 years of experience in backend or cloud software development. Must Have:
Python backend microservice development
PySpark — data processing at scale
Microservices — REST API design and inter-service communication
Data modelling — understanding of data schemas and integration patterns
Kubernetes — containerized service deployment and operations
ETL/ELT – Pipeline design and orchestration (e.g., Airflow, Step Functions, or equivalent)
SQL
AWS

Nice to Have
Healthcare data standards: HL7, DICOM
Clinical/IGT analytics platforms experience
Streaming data technologies: Kafka, Kinesis, NATS

Experience implementing CI/CD pipelines and infrastructure-as-code. Familiarity with message brokers (e.g., Kafka, NATS, RabbitMQ) for event-driven data ingestion. Understanding of data privacy regulations and secure data handling practices in healthcare. Valuable collaboration skills in cross-functional agile teams. Proficiency in leveraging AI-assisted development tools to accelerate coding and testing.

📌 Data Engineer Python Pyspark Aws Etl/elt Pipeline Thiruvananthapuram
🏢 Quest Global
📍 Thiruvananthapuram