Senior Data Engineer

Company Overview 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 diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Caring. Connecting. Growing together. Primary Responsibilities Perform all phases of software engineering including requirements analysis, application design, code development, and testing Design and implement performance and operational enhancements Design & develop reusable components, patterns, and frameworks, encouraging innovation that will enable team velocity Review code and provide feedback relative to best practices and performance improvement Conduct design and code reviews to ensure that developed code meets software engineering best practices and guidelines, unit testing, security, and scalability and maintainability guidelines Participate in Agile/Scrum methodology to deliver high‑quality software release Work with a team of software engineers for one or more Agile scrum teams assigned to work on the project Troubleshoot production support issues of post‑deployment and design solutions as required Design, code, test, debug, and document software, whilst enhancing existing components to ensure that software meets business requirements Work very closely with architecture groups to drive software solutions Contribute to the design and architecture to enable secure, scalable, and maintainable software and be able to clearly articulate the implications of design/architectural decisions, issues and plans to technology leadership Collaborate on design with other team members and product owners, both inside and outside of the scrum team. Required Skills / Attributes 5+ years of hands‑on experience with cloud data services (AWS, Azure, or GCP) 5+ years of experience in Python 5+ years of experience building and maintaining ETL/ELT pipelines in enterprise environments 5+ years of experience integrating with RESTful APIs 5+ years of experience with Agile methodologies (Scrum, Kanban) Knowledge of data governance, security, privacy, and vulnerability management Understanding of authorization protocols (OAuth) and API integration Solid proficiency in SQL, NoSQL, and data modeling Proficiency with open‑source tools such as Apache Flink, Iceberg, Spark, and PySpark Advanced Python skills for data engineering and data science (beyond Jupyter notebooks) Familiarity with big data technologies such as Spark, Hadoop, and Databricks Ability to build modular, testable, and reusable data solutions Solid grasp of data engineering concepts including: Data Catalogs Data Warehouses Data Lakes (especially Iceberg) Data Dictionaries Preferred Skills / Experience Experience with GitHub, Terraform, and GitHub Actions Experience with real‑time data streaming (Kafka, Kinesis) Experience with feature engineering and machine learning pipelines (MLOps) Knowledge of data warehousing platforms (Snowflake, Redshift, BigQuery) Familiarity with AWS native data engineering tools: Lambda, Lake Formation, Kinesis (Firehose, Data Streams) Glue (Data Catalog, ETL, Streaming) SageMaker, Athena, Redshift (including Spectrum) Demonstrated ability to mentor and guide junior engineers Seniority level Mid‑Senior level Employment type Full‑time Job function Information Technology Industries IT Services and IT Consulting Location Remote (Global) #J-18808-Ljbffr