• Lead and support the migration of ETL jobs and databases from on-premises environments to the AWS Cloud. • Build new ETL solutions if necessary and thoroughly understand existing ETL jobs. • Ensure job execution, data validation, and adherence to data compliance and business rules. • Develop ETL solutions to replicate on-premises processes in the cloud, orchestrate and validate jobs, and provide production support. • Automate and orchestrate ETL processes, applications, and APIs to optimize performance and scalability across environments. • Develop comprehensive documentation covering overall processes, data mappings, data flows, APIs, application code, and support procedures.

Role Description We’re seeking an Analytics Engineer-Databricks Engineer to lead the development of data‑driven products that power decision‑making across the system. In this senior role, you’ll guide the full analytics lifecycle while collaborating with IT ETL teams, analytics business partners, and end‑users to deliver impactful solutions. - Design, develop, and maintain analytics solutions, dashboards, and reports that deliver actionable insights to clinicians, leaders, and business stakeholders. - Integrate, organize, and transform data from multiple sources, partnering with IT teams to build and maintain scalable data models. - Analyze complex datasets to identify trends, support decision-making, and improve operational and business outcomes. - Write high-quality, maintainable code and apply analytics best practices to ensure performance, accuracy, and reliability. - Communicate findings through compelling data visualizations, presentations, and storytelling tailored to diverse audiences. - Lead and support analytics initiatives by managing priorities, documenting processes, resolving issues, and providing user training and adoption support. Qualifications - Required: Bachelor’s Degree in Engineering, Operations Research, Business, Business Analytics, Healthcare Administration, Mathematics, Statistics, Data Science, Actuarial Science or related field required OR equivalent experience of at least 5 years working in an analytics or healthcare operations setting that includes demonstrated results driving improvements using data and analytics methodologies and techniques required. - Preferred: Master’s degree in Engineering, Operations Research, Business, Business Analytics, Healthcare Administration, Mathematics, Statistics, Data Science, Actuarial Science or other related field preferred. - Relevant work experience is required. - Databricks experience is highly preferred, as this position is specific to DataBricks. Requirements - This position does not offer Visa sponsorship. Candidates must have permanent work authorization in the United States. - Remote/work from home with strong preference for candidates residing within the UPH geographies of Iowa, Illinois, & Wisconsin. Benefits - Paid time off, parental leave, 401K matching, and an employee recognition program. - Dental and health insurance, paid holidays, short and long-term disability, and more. - Pet insurance for your four-legged family members. - Early access to earned wages with Daily Pay. - Tuition reimbursement to help further your career. - Adoption assistance to help you grow your family.

• Data-Driven Culture: You will be an ambassador for our data-driven culture, taking data and shaping it to facilitate analysis, insight generation, and decision-making • Data Management: You will ingest, clean and organize raw data in a way that makes sense for both you and the team • Project Management: You will lead data projects from ingestion to reporting, showing your experience to oversee, scope, and work with ambiguity, making uncertainty certain • Collaborative Actualization: You will liaise between Business, Engineering, and Data to translate business requirements into proper data capture and schema design • Data Strategy: You will help shape the data model at Super, which will advance our broader analytics strategy and build trust within the organization • Teamwork: You will work with key stakeholders to understand existing processes and collaborate to design and implement improved and automated processes

• Set and raise the bar on analytics engineering standards. Define the patterns, testing, and review practices that keep dbt models across the business consistent, documented, and trustworthy without you personally checking every one. • Own the context layer. Bring the semantic layer (Omni) and the underlying domain models together into one place the business, human or AI, can query with confidence. • Build the domain model from first principles. Take tem's data from raw source to a structured, trusted layer that powers commercial, financial, risk, and operational decisions, not just dashboards. • Expand analytics engineering's reach across the business. Integrate new data sources, product and platform events, and the tools other departments run on, taking analytics engineering from a centralised function into new corners of the company. • Help tem think bigger. As the business looks at big bets like international expansion and new ways of bringing its technology to other companies, help build a domain layer that's ready to go with it. • Partner across the business, not just the data team. Work directly with engineers, product managers, and salespeople to understand what they're actually trying to achieve, then turn that into models that hold up under real use.