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.

Functions may include database architecture, engineering, design, optimization, security, and administration; as well as data modeling, big data development, Extract, Transform, and Load (ETL) development, storage engineering, data warehousing, data provisioning and other similar roles. Responsibilities may include Platform-as-a-Service and Cloud solution with a focus on data stores and associated eco systems. Duties may include management of design services, providing sizing and configuration assistance, ensuring strict data quality, and performing needs assessments. Analyzes current business practices, processes and procedures as well as identifying future business opportunities for leveraging data storage and retrieval system capabilities. Manages relationships with software and hardware vendors to understand the potential architectural impact of different vendor strategies and data acquisition. May design schemas, write SQL or other data markup scripting and helps to support development of Analytics and Applications that build on top of data. Selects, develops and evaluates personnel to ensure the efficient operation of the function.

Primary Responsibilities:

• Design & Build Data Infrastructure: Develop and maintain scalable data pipelines (ETL/ELT) for large-scale data processing
• Data Architecture: Lead architectural decisions for data warehousing and big data solutions
• Optimize Performance: Improve database performance, query efficiency, and data workflows
• Data Quality & Governance: Implement frameworks for data validation, monitoring, and compliance
• Collaboration: Work with data scientists, analysts, and business teams to enable analytics and machine learning
• Mentorship: Guide junior engineers and promote best practices in data engineering
• Automation & Deployment: Create automated testing and deployment processes for data systems
• Troubleshooting: Resolve complex data issues and ensure system reliability
• Analyzes and investigates
• Provides explanations and interpretations within area of expertise
• 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:

• Undergraduate degree or equivalent experience
• 7+ years of experience
• Programming: Solid in Azure Databricks, Python/Scala, ADF, Airflow, SQL; experience with Snowflake is a plus
• Data Modeling & Warehousing: Expertise in relational and NoSQL databases
• ETL Tools & Big Data: Hands-on with Spark, Hadoop, or similar frameworks
• Cloud Platforms: Azure, (or GCP) experience
• Containerization & Orchestration: Docker, Kubernetes
• Distributed Systems: Knowledge of data partitioning and parallel processing
• Data Security & Compliance: Familiarity with GDPR, HIPAA, or similar standards

Preferred Qualifications:

• Streaming Technologies: Kafka or similar message queuing systems.
  Snowflake
• AI and Machine Learning Deployment: implementing AI solutions (RAG development, Agents creation), Exposure to ML model integration
• CI/CD for Data: Jenkins or other DevOps tools for data workflows

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.

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