Clinical Data Engineer – FHIR/Oncology

Job Title: Clinical Data Engineer – FHIR/Oncology

Experience: 4–8 Years

Work Mode: Hybrid

Location: Bangalore, Pune, Gurgaon, Kolkata, Mumbai

Primary Skills:

FHIR

mCODE

Clinical Data

Secondary Skills:

ICD-O

SNOMED

LOINC

Position Overview:

We are seeking an experienced Clinical Data Engineer with strong expertise in oncology workflows, healthcare data standards, and FHIR interoperability. The role involves designing and managing scalable data pipelines, mapping oncology data to FHIR resources, and ensuring seamless integration of healthcare data across systems. The ideal candidate will have both clinical domain knowledge (oncology) and technical expertise (ETL, SQL, Python, APIs, Cloud) to support advanced healthcare interoperability and analytics initiatives.

Key Responsibilities:

Understand oncology workflows, including cancer care pathways, staging, treatment regimens, and clinical documentation.

Apply oncology-specific data standards such as mCODE (Minimal Common Oncology Data Elements), SNOMED CT, LOINC, and ICD-O.

Perform clinical data modelling, mapping oncology data elements to FHIR resources and profiles.

Work extensively with FHIR standards to integrate and transform healthcare data for interoperability.

Map, normalize, and validate incoming data to ensure consistency, completeness, and quality.

Design, develop, and maintain data pipelines with focus on scalability, reliability, and efficiency.

Implement ETL processes, data integration, and data modelling techniques.

Troubleshoot and resolve data-related issues, ensuring timely and high-quality deliverables.

Ensure robust error handling, logging, and auditing for compliance and troubleshooting.

Collaborate with cross-functional teams (data scientists, developers, healthcare professionals) to align on project requirements.

Work with healthcare datasets (EHR/EMR systems) and apply HL7 standards and APIs for data exchange.

Explore and apply cloud platforms (AWS, Azure, GCP) for healthcare data solutions.

Exposure to machine learning and healthcare analytics is a plus.

Required Skills & Qualifications

· Bachelor’s or Master’s degree in Computer Science, Health Informatics, Data Engineering, or related field.

· 4–8 years of experience in data engineering or healthcare interoperability roles.

· Strong experience with FHIR standards and oncology-specific data mapping.

· Proficiency in SQL, Python, JSON, REST APIs, and ETL frameworks.

· Hands-on experience with cloud platforms (AWS, Azure, or GCP).

· Familiarity with healthcare terminologies (SNOMED CT, LOINC, ICD-O) and datasets (EHR/EMR).

· Knowledge of HL7 standards, healthcare APIs, and interoperability protocols.

· Strong problem-solving, debugging, and data quality assurance skills.

· Excellent communication and collaboration skills to work across technical and clinical teams.

· Exposure to machine learning, analytics, or advanced healthcare technologies is an added advantage.