Senior Cloud Data Engineer - Remote

Optum Insight is improving the flow of health data and information to create a more connected system. We remove friction and drive alignment between care providers and payers, and ultimately consumers. Our deep expertise in the industry and innovative technology empower us to help organizations reduce costs while improving risk management, quality and revenue growth. Ready to help us deliver results that improve lives? Join us to start Caring. Connecting. Growing together.  

The Senior Cloud Data Engineer - Remote will be a key technical resource during the solution implementation of cloud-centric data management architecture. The primary role of the Senior Cloud Data Engineer is to take the design and technical specifications and develop effective and high-quality technical solutions that meet business requirements. The technical domain of the Cloud Data Engineer includes understanding Data Acquisition/Integration (DA/DI) best practices, tools and technologies, security in the environment, understanding of different data warehousing and dimensional modelling concepts, DI development, performance tuning and support system testing.

We are seeking an experienced Senior Cloud Data Engineer to support large-scale Cloud Data Modernization initiatives. The successful candidate will lead the migration and modernization of legacy data platforms, ETL/ELT processes, and enterprise data warehouses to cloud-native solutions leveraging Azure, Snowflake, Databricks, and modern data engineering practices.  This role combines hands-on engineering, technical leadership, and solution implementation responsibilities to deliver scalable, secure, high-quality cloud data platforms that support analytics, reporting, and operational workloads.

You'll enjoy the flexibility to work remotely* from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Primary Responsibilities:
Cloud Data Modernization

• Provide technical leadership in design and engineering for the modernization of legacy data platforms, ETL/ELT processes, and enterprise data warehouses to new technologies in the Public Cloud (AWS/Azure)
• Review and analyze existing SSIS, SQL Server, and legacy ETL implementations and develop modernization strategies
• Design, develop, and implement cloud-native data solutions utilizing Azure Data Factory (ADF), Azure Data Lake Storage Gen2 (ADLS Gen2), Snowflake, Databricks, Azure cloud services

Data Engineering & Integration

• Design and develop scalable ETL/ELT pipelines supporting batch and streaming workloads
• Create source-to-target mappings and implement data ingestion frameworks supporting structured and unstructured data
• Build and optimize cloud data warehouses, data marts, and lakehouse architectures
• Implement full and incremental load patterns, change data capture (CDC), and automated data validation processes
• Perform data profiling, data quality assessment, and root cause analysis for data issues
• Create Process Flows using diagraming tools like Visio
• Automate pipeline processes using scheduling tools like AirFlow
• Conduct ETL/ELT unit testing; participate in system and integration testing; identify and remedy solution defects

Data Architecture & Modeling

• Design and implement enterprise data warehouse solutions utilizing dimensional modeling concepts including Star schemas, Snowflake schemas, Fact and dimension design, Data pipeline architectures
• Collaborate with business and technical stakeholders to understand requirements and translate them into scalable solutions

Cloud Security & Governance

• Implement appropriate data security, privacy, governance, and compliance controls
• Ensure compliance with organizational standards for data protection, auditability, and data quality
• Proven expertise in managing highly sensitive PHI/PII, claims, provider, clinical, and member data while supporting Risk Adjustment (HCC/RAF), quality measurement programs, and ensuring HIPAA compliance, data governance, privacy, and security standards
• Establish data lineage, monitoring, and operational support processes
• Architected HIPAA-compliant Azure and Snowflake-based healthcare analytics platforms integrating Claims, Membership, Prov