Data Engineering Manager - Azure, GenAI, RAG, Agentic AI
Optum (company site, opens in a new tab)6+ yrsNoidaOn-siteDirect career pageEst. 28–45 LPA
Posted on 1 Sept
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Job description
Structured overview of role & requirements
About This Role
- Own and drive the end-to-end Machine Learning lifecycle including data ingestion, feature engineering, model training, deployment, monitoring, and governance on Azure.
- Architect, build, and operate enterprise-scale ML platforms and production-grade data pipelines using Azure Databricks, Spark, Kafka, and related technologies incorporating MLOps and automation.
- Lead design and operationalization of Agentic AI and Retrieval-Augmented Generation (RAG) pipelines with multi-modal data, ensuring scalability, security, cost optimization, and enterprise AI adoption.
Minimum Requirements
- Graduate degree or equivalent experience required.
- Minimum 6+ years of experience in Data Engineering.
- Hands-on expertise with Azure Databricks, Spark, Delta Lake, Kafka, Event Hubs, Azure Machine Learning, MLflow, MLOps, CI/CD, Azure OpenAI, Generative AI, RAG, Agentic AI.
- Proficient in Python, SQL, PySpark, GitHub Actions, Azure DevOps, Terraform/Bicep, and experience in distributed data processing and real-time data streaming on cloud-native platforms.
Ideal Candidate Profile
- Experienced in managing complex enterprise-scale AI/ML platforms on Azure with strong operational and governance rigor.
- Skilled in architecting and optimizing multi-modal data pipelines for advanced AI applications, including Agentic AI and RAG.
- Demonstrates strong technical leadership and mentoring ability aligned with best practices in cloud-native AI engineering and data governance frameworks.