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At Optum, we value the distinctive talents and perspectives each employee brings to our workplace. We foster an inclusive work environment through various initiatives like our Employee Resource Groups, which are connected internal communities that focus on sharing our diverse experiences and backgrounds, creating a greater sense of belonging.
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Optum

Primary Responsibilities:• Design and 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 and 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 and Deployment: Create automated testing and deployment processes for data systems• Troubleshooting: Resolve complex data issues and ensure system reliability• 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 soRequired Qualifications:• Undergraduate degree or equivalent experience• 9+ years of experience• Programming: Solid experience in Azure Databricks, Python/Scala, ADF, Airflow, SQL• ETL Tools & Big Data: Hands-on experience with Spark, Hadoop, or similar frameworks• Cloud Platforms: Azure, (or GCP) experience. Containerization & Orchestration: Docker, Kubernetes• Data Modeling & Warehousing: Expertise in relational and NoSQL databases• Distributed Systems: Knowledge of data partitioning and parallel processing• Data Security & Compliance: Familiarity with GDPR, HIPAA, or similar standardsPreferred Qualifications:• Programming: Experience with Snowflake• Streaming Technologies: Kafka or similar message queuing systems• AI and Machine Learning Deployment: Experience in implementing AI solutions (RAG development, Agents creation), Exposure to ML model integration• CI/CD for Data: Experience with Jenkins or other DevOps tools for data workflows

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