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.

This Data Engineering Consultant position with data science emphasis supports the ongoing digital transformation and modernization of internal audit's risk assessment, automation efforts, and risk monitoring activities. This position is responsible for supporting Internal Audit engagements with scalable, end-to-end ETL and analytic processes. Additionally, the role is responsible for working closely with data analytics teams to create robust scripted data solutions, develop and support business monitoring tools, and support existing data systems and analytic reports. This includes identifying and integrating data sources, assessing data quality, and developing and executing data analytic tools/languages to support enterprise analytical risk assessments. What's more, this position will support the Analytics-to-Insights (A2I) program within Internal Audit, helping to develop scaled statistical and machine learning models to address business research questions. This role is integral to our strategy to enable Internal Audit with data driven insights and bring value to our business partners.

The role will challenge you to leverage your data analytics skills on a variety of initiatives in a hands-on role, as well as the opportunity to develop your skills as an auditor in a matrixed and cross-functional internal audit department.

Primary Responsibilities:

• Data Engineering & Automation
  • Design, build, and maintain automated data pipelines for extracting, transforming, and loading data from diverse sources (e.g., enterprise platforms, SharePoint, NAS drives)
  • Develop scalable data models and analytical datasets to support risk surveillance, reporting, and predictive analytics
  • Implement and monitor ETL/ELT workflows to ensure data freshness, reliability, and minimal manual intervention
  • Integrate new data sources and automate ingestion processes to expand surveillance coverage and support advanced analytics
• Data Science & Modeling
  • Apply statistical and machine learning techniques to address business research questions, including risk prediction, anomaly detection, and trend analysis
  • Fit, evaluate, and deploy predictive models using structured and unstructured data to enhance decision-making capabilities
  • Collaborate with stakeholders to translate business problems into data science solutions, including feature engineering and model selection
  • Monitor model performance and retrain as needed to maintain accuracy and relevance
• Data Management & Governance
  • Ensure data quality, completeness, and consistency across all datasets used for surveillance and modeling.
    Develop and enforce validation, cleansing, and transformation procedures to support accurate analysis and model reliability
  • Implement data security and access controls in compliance with regulatory and organizational standards
  • Maintain metadata, data dictionaries, and lineage documentation for all data assets
  • Support data governance initiatives, including cataloging, retention policies, and audit readiness
• Collaboration & Communication
  • Partner with risk surveillance teams, data analysts, and audit stakeholders to understand requirements and deliver analytical-ready datasets and models
  • Collaborate with IT, data stewards, and business partners to resolve data issues and facilitate access to new sources for engineering and modeling
  • Communicate pipeline and model status, issues, and solution approaches clearly to both technical and non-technical audiences
  • Provide training and support for users on data tools, repositories, and best practices
  • Document workflows, modeling processes, and solutions for knowledge sharing and operational continuity.
• 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 regard 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:

• Program experience in Computer Science, Information Technology, Mathematics, Engineering, or related field
• 4+ years of SQL programming
• 4+ years programming in Python and/or R, including experience with data manipulation, statistical analysis, or machine learning libraries (e.g., pandas, scikit-learn, tidyverse)
• 2+ Cloud computing experience such as Azure, AWS, Databricks, and/or Spark computing
• 2+ Applied data science experience including regression analysis, classification, clustering, and machine learning model development for business insights
• 2+ years of data modeling and scaled automation experience
• 2+ years of data visualization experience using tools such as Tableau and/or PowerBI
• Solid interpersonal and analytical skills with the ability to work effectively in a matrixed team environment
• Solid oral and written communication skills, including the ability to explain technical concepts to non-technical audiences
• Familiarity with change management tools (e.g., GitHub, Jenkins, or similar)

Preferred Qualifications:

• 2+ years experience developing scalable solutions using SSIS, Data Factory, Python, or R
• Experience conducting automation involving API calls and integrating model outputs into data pipelines
• Experience working in the Healthcare Industry and/or a complex IT environment
• Financial Accounting, Auditing, or Internal Control experience

• Working knowledge of Big Data tools, Cloud platforms, and SQL Server database engineering

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.