Data Engineering Lead
RhythmX AI (company site, opens in a new tab)10+ yrsBengaluruOn-siteDirect career pageEst. 35–60 LPA
Posted 21h ago
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Job description
Structured overview of role & requirements
About This Role
- Build and optimize large-scale data pipelines for healthcare and clinical guidelines data from EHR systems, ensuring compliance with healthcare standards such as FHIR and HL7.
- Manage and orchestrate complex AI-enabled data workflows using tools like Apache Airflow and Temporal, supporting AI applications including RAG, GraphRAG, and tool calling.
- Collaborate with data scientists and backend developers to integrate, assess, and validate Gen-AI based healthcare data solutions, and lead problem-solving efforts on technical challenges.
Minimum Requirements
- Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.
- 10+ years of experience in data engineering with proficiency in Python, PostgreSQL (or variants), MongoDB, and Milvus Vector DB.
- Experience managing data pipelines from hospital EHR systems and clinical data sources adhering to healthcare standards (FHIR, HL7, Epic Clarity extracts).
- Work Experience Required: 10+ years of relevant data engineering experience. Notice period: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Demonstrated expertise in GenAI technologies including LLMs, prompt engineering and optimization, embedding techniques, and RAG implementations applied in healthcare domain.
- Strong experience with AI-native data orchestration tools (Airflow, Temporal) and Azure OpenAI stack, plus managing production-ready GenAI healthcare data solutions.
- Proven ability to handle sensitive healthcare data workflows with compliance and to support integration across offshore/onshore teams in complex environments.