Operations Engineer

Rockstar is recruiting for a fast-growing company that is a leader in the healthcare and benefits space, helping members navigate complex claims, billing, and eligibility with ease. They are a mission-driven organization that values operational excellence, data-driven decision-making, and eliminating inefficiencies through automation . This role is a key part of their Data team, focused on building reliable, scalable solutions that reduce manual work and improve accuracy across the organization.

Summary

The client is seeking an Operations Engineer to join their Data team as a strong mid-level individual contributor. This role is built for someone who can own ambiguous business problems, partner directly with cross-functional stakeholders, and turn tedious, error-prone, time-consuming manual work into elegant, reliable automations . Rather than building models, dashboards, and metrics, the successful candidate will spend their time deeply understanding how work actually gets done across the organization, documenting those processes, and designing and building solutions that meaningfully increase productivity. They will work primarily in SQL, Python and across APIs, scripting, and workflow automation tooling , and they will lean heavily on Claude and other AI tools — not just to move faster, but as core building blocks for the automations they ship. This role is not a people-management role . It is a hands-on IC role for someone who wants to find the most painful manual processes at the client and make them disappear.

Essential Duties And Responsibilities

• Own cross-functional automation projects. Partner with Operations, Member Care, Finance, Product, Engineering and leadership to understand painful manual processes, define requirements, and deliver durable solutions that eliminate or dramatically reduce that work.
• Deeply understand and document existing processes. Sit with stakeholders, map current-state workflows step by step, identify where time is being lost and errors are being introduced, and quantify the cost of the status quo so the right problems get prioritized.
• Design elegant automation solutions. Translate messy, real-world processes into clear, maintainable designs. Identify the highest-leverage opportunities for automation, choose the right approach, and account for edge cases, failure modes, and the humans who will rely on the output.
• Build, test, and maintain automations. Develop, test, document, and maintain models, scripts, integrations, and AI-powered workflows that reliably take over manual work, and keep them running as source systems and requirements change.
• Use AI tools as a core part of how you build. Use Claude and other AI tools to design and build automations — including LLM-powered workflows and agents — while validating outputs, handling errors gracefully, and protecting data quality and trust.
• Translate business am