Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy advantages, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

Primary Responsibilities

Design, develop, and maintain scalable data pipelines using Databricks (Spark / PySpark)
Orchestrate and monitor workflows using Apache Airflow for batch and incremental processing
Build and optimize ELT pipelines in Snowflake, ensuring performance, reliability, and cost efficiency
Develop production-quality Python code for data processing, transformations, and integrations
Design, build, and host APIs and data services using modern Python frameworks




Deploy and manage APIs using Azure-native services (Azure Functions, App Services, API Management)
Apply Azure cloud best practices for security, scalability, monitoring, resiliency, and cost optimization
Implement data quality checks, logging, alerting, and observability for production pipelines
Collaborate with analytics, product, and platform teams to enable downstream data consumption
Participate in architecture design, code reviews, and technical decision-making
Troubleshoot and resolve complex production issues across data pipelines and cloud infrastructure
Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and ot

📌 Senior Data Engineer (Hyderabad)
🏢 Optum India
📍 Hyderabad