Senior Data Engineering Consultant

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 benefits, 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, build, and maintain scalable ETL/ELT pipelines for ingesting and transforming data from multiple sources
• Support the implementation of a centralized data platform (data lake, lakehouse, and/or data warehouse) on Azure
• Develop and optimize data models and schemas to support reporting, analytics, and AI/ML use cases
• Enable AI and machine learning initiatives by preparing and delivering high-quality, structured datasets
• Implement data solutions using Azure services such as Data Factory, Synapse, Fabric, Data Lake, and related tooling
• Ensure data quality, integrity, and governance, including validation, monitoring, and error handling
• Optimize data pipelines and storage for performance, scalability, and cost efficiency
• Support reporting and dashboarding solutions (e.g., Power BI) through curated and accessible data layers
• Analyze and document data flows, integrations, and dependencies across systems
• Work with business and technical teams to translate requirements into scalable data solutions
• Identify opportunities for automation, reuse, and AI-driven insights across the data platform
• Participate in testing, validation, and deployment of data solutions
• Design, develop, and deploy AI-powered solutions using no-code, low-code, and advanced platforms, translating business needs into scalable applications that enhance products, workflows, and decision-making
• 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 regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so
  
  

• Undergraduate degree or equivalent experience
• 8+ years of experience in data engineering and data pipeline development
• 8+ years of experience with ETL/ELT tools and data movement frameworks
• 5+ years of experience in SQL and .Net or Java (or similar language)
• 4+ years of experience in working with large-scale, distributed data systems
• 4+ years of experience in understanding of data modeling, data warehousing, and lakehouse concepts
• 4+ years of experience in Azure Data Factory / Synapse / Fabric
• 3+ years of experience in supporting AI/ML use cases through data preparation and pipeline development
• 2+ years of experience in Azure Data Lake Storage