Senior Cloud Data Engineer – Remote

UnitedHealth Group•Eden Prairie, MN

1d•$91,700 - $163,700•Remote

About The Position

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.

Requirements

6+ years of experience in designing, developing, and implementing enterprise data warehouse and analytics solutions on prem and on cloud
3+ years of hands-on cloud data engineering experience utilizing Azure cloud technologies
3+ years of experience working as part of data engineering teams, including offshore teams, through a product life cycle – requirements, design, development, testing and deployment
Experience with Azure Data Factory (ADF), Databricks, Snowflake, ADLS Gen2, SQL Server, Python, Spark/Pyspark, ETL/ELT development
Understanding of data warehousing concepts, dimensional modeling, data quality management, data governance, data pipeline architecture
Experience designing and implementing healthcare data and analytics solutions, including large-scale cloud data modernization, data warehouse migration, platform transformation initiatives, HL7 and laboratory data processing frameworks, API-based integrations, clinical data standardization, and cloud-native healthcare interoperability platforms
Expertise in healthcare interoperability and industry standards including HL7, FHIR, X12 EDI (837/835/834), ICD-10, CPT, HCPCS, and LOINC
Comprehensive understanding of healthcare payer operations, CMS and NCQA regulatory frameworks, Population Health Management, Healthcare Economics, and FACETS-supported business processes across Claims, Membership, Eligibility, Provider, and Care Management domains
Experience implementing CI/CD and DevOps practices using GitHub and GitHub Actions
Experience working within Agile delivery methodologies
Advanced AI/GenAI expertise with tools such as Databricks Genie, GitHub Copilot, Snowflake Cortex, LLMs, prompt engineering, Azure OpenAI, Databricks Mosaic AI
Ability to provide architectural guidance and mentor engineers
Consulting-oriented background with experience aligning technology strategy to business outcomes, facilitating stakeholder discussions, defining migration approaches, and driving enterprise modernization programs
Ability to accommodate 10 – 20%25 travel when required
All employees working remotely will be required to adhere to UnitedHealth Group’s Telecommuter Policy
Candidates are required to pass a drug test before beginning employment.

Nice To Haves

Snowflake, Azure, Databricks, or Cloud Data Engineering certification
Experience with cloud data platforms across Azure, AWS, and/or Google Cloud
Experience working with healthcare claims, member, enrollment, or clinical data
Experience with streaming and event-driven architecture utilizing Kafka and Spark Structure Streaming
Experience with Infrastructure as Code (Terraform) and container technologies (Docker, Kubernetes)
Experience leading architecture assessments, developing modernization roadmaps, producing future-state architecture designs, and supporting executive-level technology strategy discussions
Demonstrated ability to meet tight deadlines, follow development standards and effectively raise critical issues with the client
Excellent analytical, problem-solving, communication, and stakeholder management skills
Demonstrated ability to work independently, manage ambiguity, and deliver high-quality solutions

Responsibilities

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
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
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
Implement appropriate data security, privacy, governance, and compliance controls
Ensure compliance with organizational standards for data protection, auditability, and data quality
Establish data lineage, monitoring, and operational support processes
Architected HIPAA-compliant Azure and Snowflake-based healthcare analytics platforms integrating Claims, Membership, Provider, Clinical, Laboratory, Pharmacy, and Care Management data
Implement CI/CD pipelines and DevOps practices using GitHub Actions and other modern delivery tools
Support Agile software delivery practices and contribute across the full development lifecycle, including: Requirements, Design, Development, Testing, Deployment, Production support
Lead the assessment of current-state data platforms and develop future-state cloud data architecture roadmaps aligned with business objectives and enterprise technology strategy
Define and document solution architecture patterns, integration approaches, data flows, and technical design specifications for enterprise-scale modernization initiatives
Create implementation roadmaps, effort estimates, technical dependencies, and migration strategies for large-scale cloud transformation programs
Provide technical leadership for cloud data engineering initiatives
Mentor junior engineers and contribute to engineering best practices
Collaborate effectively in matrixed environments with business stakeholders, architects, analysts, developers, and project teams
Proactively identify implementation risks, constraints, and improvement opportunities
Build partnership and rapport with client technical resources by demonstrating strong written and verbal communication, presentation, analytical and interpersonal skills
Ability to work closely with Business Analysts and SMEs to understand business requirements
Ability to work in a matrixed team environment with distributed responsibility across different teams
Proactive and diligent in identifying and communicating scope, design, development issues and recommending potential solutions
Partner with AI Engineering on RAG pipelines, embedding strategies, and vector stores that ground responses in EHR data, clinical documentation, and medical literature, including implementing data refresh patterns that sync with EHR updates and evidence-based guideline revisions