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:
- Senior Data Engineering Analyst
- The Senior Data Engineering Analyst is responsible for designing, building, and maintaining scalable data solutions that enable advanced analytics, AI-driven insights, and operational excellence. This role combines expertise in data engineering, cloud technologies, and DevOps practices to ensure robust, secure, and high-performing data platforms
- Data Engineering & Architecture
- Design and implement data pipelines for structured and unstructured data
- Optimize ETL/ELT processes for performance and scalability
- Develop and maintain data models supporting analytics and AI workloads
- AI & Advanced Analytics Enablement
- Integrate AI/ML models into data workflows for predictive and prescriptive analytics
- Collaborate with Data Scientists to operationalize machine learning models
- Implement feature engineering and model monitoring pipelines
- Cloud Engineering (Azure)
- Build and manage data solutions using Azure Data Services (Azure Data Factory, Synapse Analytics, Databricks, Azure Machine Learning)
- Ensure compliance with cloud security and governance standards
- Optimize cost and performance of cloud resources
- DevOps & CI/CD
- Implement CI/CD pipelines for data workflows and AI models
- Automate deployment and testing of data solutions
- Use InfrastructureasCode (IaC) tools like Terraform or Azure Resource Manager
- Operations & Maintenance
- Monitor data pipelines and AI services for reliability and performance
- Troubleshoot and resolve production issues promptly
- Maintain documentation and ensure adherence to SLAs
- 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:
- Technical Skills
- Data Engineering: SQL, Python, Spark, ETL tools
- AI/ML: Model deployment, MLOps, feature engineering
- Cloud: Azure Data Factory, Synapse, Databricks, Azure ML
- DevOps: CI/CD, Git, Docker, Kubernetes
- Operations: Azure Monitor, Datadog, incident management
Soft Skills:
- Solid analytical thinking
- Effective collaboration
- Clear communication
Preferred Qualifications:
- Experience with Azure AI services and ML pipelines
- Knowledge of data governance, security, and compliance frameworks
- Familiarity with realtime data streaming (Kafka, Event Hub)
- Undergraduate degree or equivalent experience
