Kerner Norland
Lead Data Engineer
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
India
Work mode:
Remote
Published on:
22 September 2026
What they need
Lead Data Engineer
Broad areas of responsibility:
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 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.
- 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.
- Lead, mentor, and develop a team of Data Engineers.
- Conduct code reviews, architecture reviews, and technical design discussions.
Personal Profile:
Bachelor’s degree in computer science, Information Technology, Engineering, or related discipline.
6+ years of experience in Data Engineering, Data Platform Engineering, or Data Architecture.
Experience with Apache NiFi, Airflow, dbt, Spark, Kafka, or equivalent modern data engineering tools.
Experience with Power BI or other enterprise BI platforms.
Familiarity with healthcare interoperability standards such as HL7 and FHIR.
Experience implementing data platforms for AI/ML and Generative AI workloads.
Knowledge of CI/CD, Infrastructure as Code, and DevOps practices.
Experience with containerized workloads (Docker, Kubernetes).
Pay: ₹1,500,000.00 - ₹2,400,000.00 per year
Benefits:
- Flexible schedule
- Provident Fund
- Work from home
Work Location: Remote
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