Data Engineer

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Data Engineer based in India. As a Data Engineer, you will design and develop specialized data solutions that support healthcare, clinical research, and biopharmaceutical operations. You will work at the intersection of data engineering, healthcare interoperability, regulatory compliance, and AI-driven automation. Your responsibilities will include integrating complex medical data sources, standardizing healthcare information, and building secure, reliable data processing pipelines. You will contribute to the implementation of compliant architectures for regulatory documentation and automated quality control. The role also involves developing custom Model Context Protocol (MCP) tools and orchestration layers to connect fragmented clinical and biopharma data ecosystems. This opportunity is ideal for an experienced professional who enjoys solving complex technical challenges and building scalable, secure, and accurate data solutions. You will work in a remote environment where innovation, technical excellence, and collaboration are essential.

Design, develop, and maintain robust data engineering pipelines for healthcare, clinical, and biopharmaceutical data processing, extraction, transformation, and normalization. Implement specialized healthcare data integration solutions, including DICOM metadata extraction and vectorization using tools such as dcm2bq, and integrate with Picture Archiving and Communication Systems (PACS) and Vendor Neutral Archives (VNA). Develop and optimize automated medical coding pipelines that support accurate, traceable coding workflows using standards such as ICD-10, CPT, FHIR, and HL7. Build and maintain regulatory-compliant data architectures that align with GxP requirements and 21 CFR Part 11, supporting automated regulatory document drafting, validation, and quality control processes. Develop custom Model Context Protocol (MCP) toolsets and secure agent orchestration layers to enable controlled access to siloed clinical and biopharmaceutical data sources. Establish data validation, quality assurance, and monitoring mechanisms to maintain data integrity, consistency, security, and reliability across integrated systems. Collaborate with technical and domain stakeholders to translate complex healthcare interoperability and regulatory requirements into effective engineering solutions. Identify opportunities to improve data processing efficiency, interoperability, automation, and system performance while maintaining compliance with applicable standards and regulations. Requirements At least 6 years of professional experience in data engineering or a closely related technical field. Hands-on experience with healthcare-specific data extraction, transformation, normalization, and interoperability tools, particularly dcm2bq and DICOM metadata processing. Practical knowledge of PACS and VNA archive integration and experience working with medical imaging data ecosystems. Strong understanding of healthcare data standards, including FHIR, HL7, ICD-10, and CPT, with experience developing automated medical coding or related healthcare data processing pipelines. Demonstrated experience designing or implementing GxP-compliant architectures and systems aligned with 21 CFR Part 11 requirements, particularly for regulatory documentation and quality control workflows. Deep familiarity with the Model Context Protocol (MCP), including the development of custom MCP tools and secure orchestration layers for AI-enabled data access and processing. Understanding of clinical and biopharmaceutical data environments, including the challenges associated with fragmented data sources, interoperability, security, and regulatory compliance. Strong problem-solving and analytical skills, with the ability to design reliable, scalable, and maintainable data solutions for complex technical requirements. Excellent collaboration and communication skills, with the ability to work effectively with cross-functional teams in a remote environment. A strong commitment to data accuracy, security, regulatory compliance, continuous improvement, and responsible automation. Benefits Remote work: Flexibility to work remotely from India. Contract opportunity: A contract-based engagement offering the opportunity to contribute specialized data engineering expertise. Technical challenges: Exposure to advanced healthcare interoperability, medical imaging data, regulatory systems, and AI-driven automation. Specialized expertise: Opportunities to apply and deepen knowledge of MCP, FHIR, HL7, DICOM, and regulated data architectures. Professional growth: Experience working on complex technology solutions at the intersection of healthcare, data engineering, and artificial intelligence. Inclusive workplace: A commitment to diversity, equity, inclusion, and creating an environment where professionals from different backgrounds can contribute and thrive.