Forward Deployed Engineer, Data Studio Revenue Cycle - Innovation_Delivery_Transformation

The Team This role sits within Converge for Health Care, Deloitte’s industry-focused asset studio for healthcare, and is part of Deloitte Consulting’s Innovation & Delivery Transformation (I&DT) practice. I&DT applies an engineering- and innovation-led mindset to how Deloitte builds, delivers, and scales technology-enabled solutions. Position Summary As a Forward Deployed Engineer within Converge for Healthcare, you will work directly with clients, Deloitte Consulting's broader Health Care consulting practice, and Converge for Healthcare's product and engineering teams. Together, you'll build out Data Studio's agentic use cases — starting from Deloitte's agentic and analytics platform and its unified healthcare data foundation — into production-scale capabilities in each client's environment, with a focus on revenue cycle: patient access, coding, billing, claims, denials, and accounts receivable. This is a techno-functional role: it requires both deep technical skill and deep healthcare domain knowledge, brought together to adapt agentic capabilities to the specific workflows, data, and nuances of each client. You'll operate at the intersection of client delivery, applied engineering, and product feedback: engaging with clients and Health Care consulting teams both pre- and post-sale, and partnering with Converge for Healthcare's product and engineering teams to translate f [... source excerpt omitted ...] sales cycle — running technical discovery, demonstrations, and use-case fit assessments — such as denial prevention, prior authorization automation, or AR follow-up — that qualify client needs and shape a credible path to production value. Agentic use case development. Work hand-in-hand with clients to build out agentic use cases on Data Studio — sometimes adapting and extending Deloitte's library of proven use cases, other times building greenfield to solve a client-specific problem — such as automating denial appeals or accelerating cash application — engineering toward durable, production-scale capabilities rather than one-off demonstrations. Data readiness for agentic use [... source excerpt omitted ...] cases. Define the data and context each agentic use case depends on to perform reliably, confirm the unified data foundation can support it, and partner with data engineering and client teams to close any gaps — owning what the use case needs to work, not the underlying pipelines that feed the foundation. Client enablement & value realization. Support client training, onboarding, and adoption activities, and stay engaged post-launch to help identify expansion opportunities grounded in real usage. Field-to-product feedback. Capture recurring client needs, data patterns, and delivery learnings, and translate them into concrete agentic capability requests and reusable extension