Join Optum, a global leader in healthcare technology, dedicated to improving lives through innovative solutions. We foster a culture of inclusion, collaboration, and continuous growth. Advance global health optimization by connecting individuals with essential care, pharmacy benefits, and data resources.

This Principal Data Engineering role is pivotal in shaping the future of our data platforms. You will be instrumental in driving technological advancements and ensuring the highest standards of engineering excellence within our dynamic team. Contribute to a mission that impacts millions, promoting healthier lives and a more effective healthcare system.

Architect and implement cutting-edge cloud-native data platforms, including Azure Data Lake, Databricks, and Snowflake, supporting both batch and streaming data processes.

Develop and maintain robust data pipelines utilizing Python/Scala, Spark, SQL, and Kafka, managed by orchestration tools like Azure Data Factory.

Design and deploy REST/GraphQL APIs for curated data products, machine learning inference, and feature services, enabling seamless data access.

Continuously optimize platforms for cost, performance, and reliability, while implementing comprehensive observability solutions such as lineage, logging, metrics, and alerting.

Provide technical leadership, mentoring a team of engineers, defining coding standards, conducting code reviews, and setting engineering OKRs.

Translate complex business needs into scalable data solutions, effectively manage stakeholder expectations, and ensure timely delivery of projects.

Possess a Bachelor's degree in Computer Science, Engineering, or a related technical discipline.

Bring 12+ years of extensive experience in data engineering and data product development, with a proven track record in technical leadership roles.

Demonstrate hands-on expertise in architecting, building, and scaling modern data platforms for analytics, AI, and real-time APIs.

Showcase practical experience with AI tools and platforms, including building and deploying AI models leveraging LLM, RAG, and Gen AI.

Master data engineering principles with proficiency in Azure, Apache Spark, Databricks (using Scala and Python), and Azure Data Factory.

Possess solid experience with both SQL and NoSQL databases for efficient data management and querying.

Exhibit strong proficiency with Git or similar version control systems.

Familiarity with Agile methodologies, unit testing, and test automation frameworks is essential.