Join Optum, a global leader dedicated to improving health outcomes through innovative technology. We connect individuals with essential care, pharmacy benefits, data, and resources, fostering healthier lives. Our inclusive culture is supported by talented colleagues, comprehensive benefits, and abundant career development opportunities. Make a significant impact on communities worldwide as we advance health optimization on a global scale. Together, we will Care, Connect, and Grow.

This role focuses on advancing health optimization through cutting-edge data engineering solutions.

Engage actively in the scrum process to deliver features on schedule. Collaborate with cross-functional teams, architects, and product stakeholders to grasp scope and design requirements, providing essential product support.

Gain a deep understanding of product architecture and upcoming features, contributing innovative improvement ideas and proof-of-concepts. Responsibilities span database architecture, engineering, design, optimization, security, and administration, alongside data modeling, big data development, ETL, storage engineering, data warehousing, and data provisioning.

Responsibilities may encompass Platform-as-a-Service and Cloud solutions, with a focus on data stores and their ecosystems. Duties include managing design services, offering sizing and configuration assistance, ensuring stringent data quality, and conducting needs assessments.

Analyze current business practices and identify future opportunities for leveraging data storage and retrieval systems. Manage vendor relationships to assess the architectural impact of different strategies and data acquisition methods. May involve schema design, SQL scripting, and supporting the development of analytics and applications built on data.

Analyze and investigate data intricacies, providing expert explanations and interpretations. Ensure compliance with employment contracts, company policies, and directives, including flexibility in work arrangements and adaptability to evolving business environments.

A Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related discipline is required.

Proficiency in DevOps, Big Data implementation, Apache Spark, and Azure Cloud is essential. Expertise includes large-scale data processing using PySpark within the Azure ecosystem and implementing self-service analytics platforms with ETL frameworks on Azure.

Demonstrated experience in building ML models, deep data analysis including source data profiling and mapping, and constructing data pipelines using ADF/Azure Databricks is crucial. Proven hands-on experience with large-scale data warehouses and data migration from legacy systems to cloud solutions is expected.

Strong skills in SQL and complex query writing are necessary. Excellent problem-solving abilities and effective communication skills are vital for success in this role. Candidates should exhibit a proven ability to learn and adapt to new data technologies.