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.

Data engineering 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. 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:

• Automation and Data Modeling
  • Design, build, and maintain automated data pipelines for extracting, transforming, and loading data from diverse sources (enterprise platforms, SharePoint, NAS drives, etc.)
  • Develop robust and scalable data models to support risk surveillance analytics and reporting needs
  • Implement and maintain workflows for scheduling and monitoring ETL/ELT jobs to ensure data freshness and reliability
  • Utilize scripting and workflow automation tools to reduce manual intervention in data movement and processing
  • Integrate new data sources and automate ingestion processes to expand surveillance coverage
• Data Management and Governance
  • Ensure data quality, completeness, and consistency across all risk surveillance datasets
  • Develop and enforce data validation, cleansing, and transformation procedures to support accurate analysis
  • Implement data security and access controls in compliance with regulatory and organizational standards
  • Maintain detailed metadata, data dictionaries, and lineage documentation for all data assets
  • Support data governance initiatives, including data cataloguing, retention policies, and audit readiness
• Collaboration and Communication
  • Partner with Risk Surveillance partners, data analysts, and audit teams to understand requirements and deliver analytical-ready datasets
  • Collaborate with IT, data stewards, and business partners to resolve data issues and facilitate access to new data sources
  • Communicate data pipeline status, issues, and solution approaches clearly to both technical and non-technical stakeholders
  • Provide training and support for users on data tools, repositories, and best practices
  • Document data workflows, 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:

• Overall 8+ years of program experience in Computer Science, Information Technology, Mathematics, Engineering, Data Analytics or related field
• 4+ years of SQL programming
• 4+ years programming in Python and/or R
• 2+ years of data modeling and scaled automation experience
• 2+ years of data visualization experience (Tableau and/or PowerBI)
• Solid interpersonal and analytical skills while working effectively with a matrixed team

• Solid oral and written communication skills

   

Preferred Qualifications:

• 2+ years experience in developing scalable solutions with SSIS, Data Factory, Python, or R
• Extensive program experience in Computer Science, Information Technology, Mathematics, Engineering, or related field
• Internal Audit / Control experience
• Cloud computing experience including Azure, AWS, Databricks, and/or Spark computing
• Experience working in a Healthcare Industry and or a complex IT environment
• Experience with conducting automation surrounding API calls
• Working knowledge of Big Data tools, Cloud platforms, SQL Server database engineering
• Data Science experience including regression analysis and machine learning techniques
• Change management tool experience (e.g., Github, Jenkins, or similar)

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.

#njp