Software Engineering Lead - Python, DevOps

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 seeking a highly skilled and experienced Data Engineer / AI Builder to lead the development of scalable data infrastructure and pipelines that support our machine learning initiatives. This role is critical in enabling data-driven decision-making and deploying intelligent systems across the organization. You will collaborate with cross-functional teams to ensure data quality, model reliability, and infrastructure scalability.

• Architect and build scalable, reliable data pipelines for batch and real-time ML workflows
• Design and manage feature stores, data lakes, and data warehouses optimized for ML use cases
• Collaborate with data scientists and ML engineers to deploy models into production environments
• Implement CI/CD pipelines for data workflows and model deployment
• Monitor and maintain data quality, pipeline health, and model performance in production
• Lead adoption of cloud-native data platforms and big data technologies
• Mentor junior engineers and promote best practices in data engineering and MLOps
• Ensure compliance with data governance, security, and privacy standards
• 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

• Bachelor's or Master's degree in Computer Science, Data Engineering, or related field
• 5+ years of experience in data engineering or ML infrastructure roles
• Solid experience with cloud platforms (AWS, GCP, Azure) and infrastructure-as-code tools
• Proficiency in Python, SQL, and one or more JVM-based languages (e.g., Scala, Java)
• Deep understanding of ML lifecycle, data versioning, and model deployment strategies
• Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, etc.)
• Proven excellent problem-solving, communication, and leadership skills

• Experience with distributed computing frameworks (e.g., Spark, Dask)
• Hands-on experience with real-time data processing tools (Kafka, Flink)
• Exposure to data governance frameworks and compliance standards (GDPR, HIPAA, etc.)
• Knowledge of containerization and orchestration (Docker, Kubernetes)