Job Description
Responsibilities
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- Own and evolve the enterprise data architecture supporting operational, analytical, and AI workloadsn
- Design scalable data platforms for transactional databases, analytical data warehouses/lakehouses, and AI/ML data pipelinesn
- Define data models, integration standards, metadata management, and data lifecycle strategiesn
- Establish best practices for data engineering, architecture, performance optimization, scalability, reliability, and maintainabilityn
- Evaluate and recommend emerging technologies and architectural improvementsn
- Design, develop, and optimize robust ETL/ELT pipelines for structured and unstructured datan
- Build reliable batch and real-time data integration pipelines from EHRs, Practice Management Systems, APIs, flat files, and third-party healthcare applicationsn
- Develop and optimize workflows using tools such as Apache NiFi or equivalent orchestration platformsn
- Ensure high data quality, integrity, consistency, lineage, and observability across all data platformsn
- Support relational, NoSQL,



and distributed data platformsn
- Design and maintain data platforms supporting Business Intelligence, advanced analytics, and machine learning workloadsn
- Build data pipelines that enable AI/ML model training, feature engineering, vector databases, Retrieval-Augmented Generation (RAG), and LLM/SLM applicationsn
- Collaborate with Data Scientists and AI Engineers to operationalize ML models and AI solutionsn
- Support MLOps and data versioning best practicesn

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nQualifications/Criteria
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- Bachelor’s degree in computer science, Software Engineering, or a related field.n
- 10+ years of experience in Data Engineering, Data Platform Engineering, or Data Architecture.n
- Minimum 5 years of experience working with US Healthcare data, preferably Revenue Cycle Management (RCM), Claims, EHR, or Healthcare Analytics.n
- Equivalent practical experience with demonstrated techni

📌 Lead Data Engineer (Hubballi)
🏢 HealthRecon Connect
📍 Hubballi