Lead Data Engineer

HealthRecon Connect; India; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

HealthRecon Connect seeks a seasoned Data Architect/Engineer to own and evolve the enterprise data architecture supporting operational, analytical, and AI workloads.

You will design scalable data platforms for transactional databases, data warehouses, and AI/ML data pipelines, defining standards, metadata, and data lifecycle strategies. Strong SQL, data modeling, and healthcare data experience are required.

Qualifications

• Bachelor’s degree in computer science, Software Engineering, or a related field.
• 10+ years of experience in Data Engineering, Data Platform Engineering, or Data Architecture.
• Minimum 5 years of experience working with US Healthcare data, e.g. RCM, Claims, EHR, or Healthcare Analytics.
• Strong expertise in SQL and data modeling.
• Equivalent practical experience with demonstrated technical leadership will also be considered.

Responsibilities

• Own and evolve the enterprise data architecture supporting operational, analytical, and AI workloads.
• Design scalable data platforms for transactional databases, analytical data warehouses/lakehouses, and AI/ML data pipelines.
• Define data models, integration standards, metadata management, and data lifecycle strategies.
• Establish best practices for data engineering, architecture, performance optimization, scalability, reliability, and maintainability.
• Build robust ETL/ELT pipelines for structured and unstructured data.

Skills

SQL proficiency

Data modeling

Data architecture

Leadership / mentorship

Healthcare data domain

ETL/ELT design

Education

Bachelor’s degree in CS / related

Tools

PostgreSQL

SQL Server

MySQL

Oracle

Job description

• Own and evolve the enterprise data architecture supporting operational, analytical, and AI workloads
• Design scalable data platforms for transactional databases, analytical data warehouses/lakehouses, and AI/ML data pipelines
• Define data models, integration standards, metadata management, and data lifecycle strategies
• Establish best practices for data engineering, architecture, performance optimization, scalability, reliability, and maintainability
• Evaluate and recommend emerging technologies and architectural improvements
• Design, develop, and optimize robust ETL/ELT pipelines for structured and unstructured data
• Build reliable batch and real-time data integration pipelines from EHRs, Practice Management Systems, APIs, flat files, and third-party healthcare applications
• Develop and optimize workflows using tools such as Apache NiFi or equivalent orchestration platforms
• Ensure high data quality, integrity, consistency, lineage, and observability across all data platforms
• Support relational, NoSQL, and distributed data platforms
• Design and maintain data platforms supporting Business Intelligence, advanced analytics, and machine learning workloads
• Build data pipelines that enable AI/ML model training, feature engineering, vector databases, Retrieval-Augmented Generation (RAG), and LLM/SLM applications
• Collaborate with Data Scientists and AI Engineers to operationalize ML models and AI solutions
• Support MLOps and data versioning best practices

Qualifications/Criteria

• Bachelor’s degree in computer science, Software Engineering, or a related field.
• 10+ years of experience in Data Engineering, Data Platform Engineering, or Data Architecture.
• Minimum 5 years of experience working with US Healthcare data, preferably Revenue Cycle Management (RCM), Claims, EHR, or Healthcare Analytics.
• Equivalent practical experience with demonstrated technical leadership will also be considered.
• Strong expertise in SQL and data modeling.
• Hands‑on experience with relational databases (PostgreSQL, SQL Server, MySQL or Oracle) and analytical databases / warehouses.
• Experience building the the