Join Optum, a global leader in healthcare, where technology drives our mission to improve lives and optimize health outcomes. As part of our inclusive culture, you'll collaborate with talented peers, access comprehensive benefits, and find ample career development opportunities. This role is integral to advancing health optimization on a global scale, focusing on the power of data to transform care delivery and enhance patient well-being.

We are seeking a skilled Data Engineer with specific healthcare industry experience. Your expertise will be crucial in implementing and managing robust, scalable, and secure data solutions. These solutions will transform raw data into actionable insights, supporting a wide array of analytical needs for our clients and partners across numerous health domains. You will be instrumental in building quality and efficiency into every stage of the data lifecycle.

Drive the end-to-end data engineering lifecycle, from initial research and concept validation through design, development, rigorous testing, and ongoing maintenance of data management solutions. Leverage deep knowledge of diverse data management technologies to spearhead impactful data engineering projects.

Lead data acquisition initiatives, effectively gathering information from various structured and semi-structured source systems. This data will populate our client data warehouses and fuel analytics across diverse healthcare sectors. Employ a combination of ETL/ELT methodologies to extract complex relational and dimensional data, preparing it for DataMart loading and aggregate reporting.

Focus on eliminating unnecessary complexity and interdependencies in data systems. Proactively detect and resolve data quality issues, identifying root causes, implementing effective fixes, and managing data audits to prevent future challenges. Streamline data integration efforts to enhance efficiency, reliability, and overall data value.

Champion and facilitate the evolution of best practices for data acquisition, transformation, storage, and aggregation, addressing current needs and mitigating future risks. Develop data transformations that precisely meet business requirements and other constraints. Collaborate with the broader analytics organization to propose enhancements to data systems and platform architecture.

Support the implementation of a modern data framework to facilitate business intelligence reporting and advanced analytics. Prepare high-level and detailed technical design documents incorporating best practices for efficient data ingestion, transformation, and movement. Utilize DevOps tools for code versioning and deployment, and leverage data pipeline monitoring tools to identify integrity issues before they impact users.

Continuously contribute to technical debt reduction, process transformation, and overall system optimization. Maintain high-quality documentation of data definitions, transformations, and processes to ensure transparency, governance, and security. Ensure all solutions align with business needs for security, scalability, and reliability. Enhance productivity by utilizing enterprise-approved AI tools for workflow streamlining and automation, staying abreast of emerging trends for continuous improvement and strategic innovation.

A Bachelor's Degree in a related field such as Information Technology, Engineering, Mathematics, Computer Science, or Analytics is required. Possess at least 3 years of hands-on experience with Microsoft Azure Cloud, Azure Data Factory, Data Bricks, and proficiency in Spark, Scala, or Python. Additionally, have 3+ years of combined experience in data engineering, encompassing ingestion, normalization, transformation, aggregation, structuring, and storage.

Demonstrate 3+ years of experience working with industry-standard relational, dimensional, or non-relational data storage systems. Have 3+ years of experience managing data assets using SQL, Python, Scala, VB.NET, or similar querying/coding languages. A minimum of 2 years of experience designing robust ETL/ELT solutions is also essential.

Crucially, candidates must possess at least 2 years of experience working with healthcare data or data specifically supporting healthcare organizations. Preferred qualifications include Epic certifications in specific modules, extensive experience in creating Source to Target Mappings, and a proven track record in designing ETL for data warehouse integrations. Experience with Epic Clarity/Caboodle or Cerner Millennium/HealthEintent is highly regarded.