Senior Consultant Business Systems

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 inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

Technical Leadership and Delivery Lead complex data engineering workstreams from intake through production release, balancing delivery velocity, architectural quality, and measurable business outcomes Provide hands-on technical direction to junior engineers and peer developers, including design reviews, code reviews, delivery sequencing, and issue resolution Translate finance analytics, reporting, and AI/ML requirements into scalable data engineering designs, implementation plans, and release-ready solutions Pipeline Engineering and Data Platform Modernization Architect, build, and maintain distributed data pipelines using Azure Data Factory, Spark/PySpark, SQL, Python, Snowflake, and Databricks to process large-scale batch and streaming datasets Migrate legacy relational or warehouse-based pipelines to cloud-native and distributed architectures that improve performance, scalability, resiliency, and cost efficiency Design and implement data lake and lakehouse patterns that support raw, curated, and consumption-layer datasets for analytics, reporting, and downstream AI/ML use cases Cloud Infrastructure and Platform Engineering Design and support cloud infrastructure patterns for data engineering workloads, including Azure Data Lake, storage organization, compute configuration, network-aware platform integration, environment promotion, and secure service connectivity Partner with cloud infrastructure, security, and architecture teams to ensure data platforms follow enterprise standards for identity, access control, secrets management, monitoring, scalability, and resiliency Apply infrastructure-as-code, environment configuration, deployment automation, and platform reliability practices where appropriate to improve repeatability, auditability, and operational support Orchestration, Automation, Reliability, and DevOps Implement monitoring, alerting, error handling, runbooks, and incident triage practices that improve pipeline reliability and reduce operational overhead Apply CI/CD best practices using Azure DevOps, GitHub, or equivalent tooling, including source control, automated testing, code review, release management, and controlled environment promotion Optimize pipeline performance and cloud consumption through capacity-aware design, scheduling strategy, partitioning, compute right-sizing, and cost-conscious engineering decisions Data Modeling, Governance, and Quality Design scalable data models and transformation patterns that support trusted finance data products across raw, curated, and consumption layers Establish data contracts, SLAs, validation rules, reconciliation checks, and data quality controls to ensure consistency and trust across downstream consumers Support secure and compliant handling of sensitive finance data, including access patterns, governance alignment, auditability, metadata documentation, and controlled release processes Stakeholder Collaboration and Analytics Enablement Collaborate with finance business partners, analytics teams, architects, product owners, and platform teams to prioritize work, resolve dependencies, and communicate delivery status and risks Enable analytics and AI/ML solutions by ensuring curated datasets are reliable, discoverable, performant, and fit for downstream reporting, modeling, and decision-support use cases Comply with the terms and conditions of the employment