Data Engineer -Health Care
Persistent Systems Limited (company site, opens in a new tab)8–12 yrsPuneHybridDirect career pageEst. 20–35 LPA
Posted on 10 Sept
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and maintain scalable data pipelines, enterprise data warehouses, data lakes, and cloud-native data platforms primarily on Azure and Databricks.
- Develop ETL/ELT processes and data models to support analytics, reporting, AI/ML, and Generative AI initiatives in healthcare domain.
- Ensure data quality, security, performance, and compliance while implementing automation, monitoring, and CI/CD practices across data platforms.
Minimum Requirements
- 8 to 12 years of experience in Data Engineering, Data Warehousing, or Big Data development.
- Strong expertise in SQL, Python, Azure cloud services (including Azure Data Factory, Synapse, Databricks), and experience with ETL/ELT pipelines.
- Knowledge and experience in healthcare domain (payer/provider, claims, operations) preferred but not strictly mandatory.
- Experience with data governance, security, CI/CD pipelines, DevOps practices, and familiarity with Generative AI and Large Language Models.
Ideal Candidate Profile
- Experienced with building large scale, cloud-native, and automated data platforms supporting analytics and AI/ML workloads in healthcare or related industries.
- Demonstrates strong ownership, stakeholder collaboration, and ability to translate business requirements into effective technical data solutions.
- Comfortable leveraging and adopting enterprise-approved AI tools and emerging AI capabilities to improve data engineering productivity and quality.