Senior Manager Data Engineering

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.

We are looking for a hands-on Data Engineering & AI Lead to own the end-to-end data strategy, AI solutioning, and engineering execution for the NICE Reporting ecosystem. This individual will architect scalable data pipelines, build and deploy AI-driven solutions, lead a team of engineers, and partner with business stakeholders to deliver intelligent, automated reporting capabilities. The role demands someone who can strategize, build, and deliver - not just plan.

Primary Responsibilities:

• Define and execute the Data engineering and AI strategy for NICE Reporting including data sourcing, pipeline architecture, automation, and migration to modern reporting platforms
• Design, develop, and optimize end-to-end data pipelines ensuring data accuracy, performance, and scalability across the reporting ecosystem
• Strategize and recommend AI-enabled solutions that improve data quality, reduce manual effort, and accelerate insight delivery for the reporting domain
• Drive automation of manual reporting processes, reduce cycle times, and improve operational efficiency across the reporting lifecycle
• Establish and enforce data quality frameworks, governance models, and monitoring standards across all data assets
• Lead the transition from legacy to modern cloud-based architectures, ensuring seamless migration with minimal disruption
• Mentor and guide a team of junior resources and drive delivery, establish best practices, and build a culture of innovation and continuous improvement
• Partner with product management, business analysts, and stakeholders to translate business requirements into scalable data and AI solutions
• 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

Required Qualifications:

• 10+ years in Data Engineering/ Data science with 3+ years in a technical lead or senior individual contributor role
• 5+ years of hands-on AI/ML experience  building, training, and deploying models in real-world environments and experience in using LangChain, Langraph, RAG, MCP and Vector Databases in building solution
• Hands-on experience with large-scale data pipeline development, data modeling, and data warehousing
• Proven experience designing and delivering complex LLM-based or agent-driven systems in production and practical experience in applying AI/ML techniques to solve business problems classification, prediction, automation, or intelligent search
• Experience working with Large Language Models (LLMs) and building AI-powered applications using modern AI frameworks and tools
• Experience with data migration transitioning from legacy systems to modern cloud-based architectures
• Proven solid expertise in Python, SQL, and cloud-based data engineering platforms (Azure preferred)
• Proven comfort with relevant libraries and tools (pandas, numpy, matplotlib or ggplot2, etc. for analysis; scikit-learn or similar for modeling). Solid understanding of statistical concepts (e.g., significance testing, distributions, regression analysis) and when to apply them
• Demonstrated ability to lead and mentor engineering teams with hands-on coaching and technical direction
• Proven excellent communication skills ability to present technical solutions clearly to business stakeholders and leadership

Preferred Qualifications:

• Experience in healthcare or insurance - familiarity with claims, provider operations, or contact center reporting
• Experience building conversational AI or agent-based solutions for enterprise use cases
• Knowledge of MLOps practices and model lifecycle management tools
• Proven exposure and hands on experience in Data engineering and AI/ML practices
• Proven exposure to contact center systems (NICE, IVR/ACD) or operational analytics

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.