Sr. Data Analyst - Optum Financial - Remote

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.

Our team, within Optum Financial Advanced Intelligence & Analytics, focuses on delivering scalable, data-driven solutions that support financial services and healthcare operations. We build and maintain curated datasets, automated file pipelines, and reporting solutions that enable operational insights, regulatory reporting, and improved decision-making across the organization. Our work directly supports enterprise initiatives by ensuring reliable, high-quality data assets that downstream teams depend on.

The Senior Data Analyst is responsible for designing, building, and maintaining scalable data solutions that support analytics, reporting, and operational use cases. This includes designing and building curated datasets that power downstream reporting and analytics, ensuring data integrity, consistency, and usability across stakeholder needs.

This role requires strong hands on experience with Databricks, including file automation, dataset development, pipeline creation, and CI/CD processes. The ideal candidate will work closely with data engineers, analysts, and business partners to deliver reliable, well governed data assets and maintain production ready data solutions that enable insight generation and decision making.
 

You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges.

Primary Responsibilities:

• Design, build, and maintain data pipelines and workflows using Databricks (SQL, PySpark)
• Develop and manage automated file ingestion and transformation processes, including scheduled and event driven file automation
• Design and build curated datasets that power downstream reporting and analytics, ensuring data integrity, consistency, and usability across stakeholder needs
• Maintain and optimize production data pipelines and reporting jobs, including monitoring, troubleshooting, and ensuring reliable end to end data delivery
• Implement and support CI/CD pipelines for data assets using version control and automated deployment practices
• Collaborate with cross functional teams to understand data requirements and translate them into scalable technical solutions
• Monitor, troubleshoot, and optimize data pipelines for performance, reliability, and cost efficiency
• Ensure data quality, validation, documentation, and adherence to enterprise data governance standards
• Support analytics and reporting teams by enabling trusted data sources for downstream tools (e.g., Power BI)
• Participate in code reviews, technical design discussions, and knowledge sharing sessions
• Contribute to continuous improvement of data engineering and analytics best practices

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required Qualifications:

• 3+ years of experience in data analytics, data engineering, or a related role 
• Solid hands on experience with Databricks, including Databricks SQL and PySpark
• Solid SQL skills and experience working with large, structured datasets
• Experience building and maintaining data pipelines, datasets, and automated workflows
• Working knowledge of CI/CD practices and version control systems (e.g., Git)
• Proven ability to independently analyze problems, design solutions, and deliver results
• Proven solid communication skills and ability to collaborate with both technical and non technical stakeholders

Preferred Qualifications:

• Experience working in cloud based data platforms and enterprise data lake or lakehouse architectures
• Exper