Senior Cloud Data Engineer – Remote

UnitedHealth Group•Eden Prairie, MN

12h•$91,700 - $163,700•Remote

About The Position

Optum Insight is hiring a Senior Cloud Data Engineer to support large-scale cloud data modernization initiatives. The role provides technical leadership and hands-on engineering to migrate and modernize legacy data platforms, ETL/ELT processes, and enterprise data warehouses into scalable, secure cloud-native solutions. The engineer translates designs and technical specifications into high-quality solutions supporting analytics, reporting, and operational workloads, using technologies including Azure, Snowflake, and Databricks. The position involves assessing current-state platforms and defining future-state architectures, modernization roadmaps, migration strategies, implementation plans, and technical designs. It also covers data ingestion and integration, cloud data warehouses and lakehouse architectures, data modeling, pipeline development and optimization, testing, security, governance, DevOps, and production support. The engineer collaborates with business and technical stakeholders, mentors junior engineers, and provides guidance across the software delivery lifecycle. The role is remote within the U.S. Employees hired in the Minneapolis or Washington, D.C. area must work in the office at least four days per week. Travel of 10–20% may be required. Remote employees must follow UnitedHealth Group’s Telecommuter Policy.

Requirements

At least 6 years of experience designing, developing, and implementing enterprise data warehouse and analytics solutions on-premises and in the cloud.
At least 3 years of hands-on cloud data engineering experience using Azure cloud technologies.
At least 3 years of experience working on data engineering teams, including offshore teams, across requirements, design, development, testing, and deployment.
Experience with Azure Data Factory, Databricks, Snowflake, ADLS Gen2, SQL Server, Python, Spark/PySpark, and ETL/ELT development.
Understanding of data warehousing, dimensional modeling, data quality management, data governance, and data pipeline architecture.
Experience designing and implementing healthcare data and analytics solutions, including cloud modernization, data warehouse migration, platform transformation, HL7 and laboratory data processing, API-based integrations, clinical data standardization, and cloud-native healthcare interoperability platforms.
Expertise in healthcare interoperability and standards including HL7, FHIR, X12 EDI (837/835/834), ICD-10, CPT, HCPCS, and LOINC.
Understanding of healthcare payer operations, CMS and NCQA regulatory frameworks, Population Health Management, Healthcare Economics, and FACETS-supported Claims, Membership, Eligibility, Provider, and Care Management processes.
Experience implementing CI/CD and DevOps practices using GitHub and GitHub Actions.
Experience working with Agile delivery methodologies.
Advanced AI/GenAI expertise using tools such as Databricks Genie, GitHub Copilot, Snowflake Cortex, LLMs, prompt engineering, Azure OpenAI, or Databricks Mosaic AI.
Ability to partner with AI Engineering on RAG pipelines, embedding strategies, and vector stores grounding responses in EHR data, clinical documentation, and medical literature, including data refresh patterns synchronized with EHR updates and evidence-based guideline revisions.
Ability to provide architectural guidance and mentor engineers.
Consulting-oriented background aligning technology strategy with business outcomes, facilitating stakeholder discussions, defining migration approaches, and driving enterprise modernization programs.
Ability to accommodate 10–20% travel when required.

Nice To Haves

Certification in Snowflake, Azure, Databricks, or Cloud Data Engineering.
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 using Kafka and Spark Structured 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.
Ability to meet tight deadlines, follow development standards, and effectively raise critical issues with clients.
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 modernizing legacy data platforms, ETL/ELT processes, and enterprise data warehouses to public-cloud technologies.
Review existing SSIS, SQL Server, and legacy ETL implementations and develop modernization strategies.
Design, develop, and implement cloud-native data solutions using Azure Data Factory, ADLS Gen2, Snowflake, Databricks, and Azure services.
Design and develop scalable batch and streaming ETL/ELT pipelines.
Create source-to-target mappings and data ingestion frameworks for structured and unstructured data.
Build and optimize cloud data warehouses, data marts, and lakehouse architectures.
Implement full and incremental load patterns, change data capture, and automated data validation.
Perform data profiling, data-quality assessments, and root-cause analysis for data issues.
Create process flows using diagramming tools such as Visio and automate pipeline processes using scheduling tools such as Airflow.
Conduct ETL/ELT unit testing, participate in system and integration testing, and identify and remedy solution defects.
Design and implement enterprise data warehouse solutions using dimensional modeling, including star and snowflake schemas, fact and dimension design, and data pipeline architectures.
Collaborate with business and technical stakeholders to understand requirements and translate them into scalable solutions.
Implement data security, privacy, governance, and compliance controls and ensure adherence to standards for data protection, auditability, and data quality.
Manage sensitive healthcare data, including PHI/PII, claims, provider, clinical, and member data, while supporting risk adjustment and quality measurement programs and HIPAA compliance.
Establish data lineage, monitoring, and operational support processes.
Implement CI/CD pipelines and DevOps practices using GitHub Actions and other modern delivery tools.
Contribute across the Agile software delivery lifecycle, including requirements, design, development, testing, deployment, and production support.
Assess 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.
Create implementation roadmaps, effort estimates, technical dependencies, and migration strategies for large-scale cloud transformation programs.
Mentor junior engineers and contribute to engineering best practices.
Collaborate with stakeholders, architects, analysts, developers, and project teams in matrixed environments.
Identify implementation risks, constraints, and improvement opportunities; communicate issues and recommend solutions.
Build rapport with client technical resources through written and verbal communication, presentations, analysis, and interpersonal collaboration.
Work with Business Analysts and subject matter experts to understand business requirements.
Provide architectural guidance, navigate ambiguity, and resolve implementation challenges with minimal supervision.