Senior Forward Deployed Data Engineer

Transform healthcare with us. At Solstice Analytics, we're redefining what's possible with Generative AI in healthcare. Our infrastructure provides the guardrails for safe AI governance, healthcare-specific agent creation, and real-time algorithm monitoring — working alongside leading health systems to drive real change. This is more than just a job. It's an opportunity to build the future of AI in healthcare, solve complex challenges, and make a lasting impact on patient care. If you're ambitious, innovative, and ready to move fast, we'd love to have you on board. Join us in shaping the future of healthcare. About Forward-Deployed Engineering at QH. Data Modernization is a forward-deployed function. Every role on this team — leadership and IC alike — works directly with health system customers, on-site and in their environments, throughout the engagement. This is not a back-office data role: you'll sit with the customer's data and IT teams, present your work to their technical leadership, and be accountable for outcomes they can see. All roles are Senior/Staff level or higher. Note on platform specialization: We are hiring Senior / Staff Data Engineers who each own deep expertise in one of our three target platforms — Databricks , Snowflake , or Microsoft Fabric . This single posting covers all three seats; we'll match you to the platform where your depth is strongest during the process. The core of the role — landing health system data in a modern lakehouse and serving as the platform-specific technical lead on an engagement — is the same across all three. Job Summary This is the role where the data actually moves. As a Senior Forward Deployed Engineer on the Data Modernization team, you own the platform-specific build that takes a health system from legacy connectivity — flat files, manual SFTP, a half-finished Clarity database — to a modern, AI-ready lakehouse that can serve our agentic AI workflows at full speed. You are the deep platform expert for your stack. During an active engagement, you serve as the platform-specific technical lead under the Principal Solutions Architect: you own the ingestion, the medallion architecture, the governance configuration, and the data-sharing pattern on your platform. Between engagements, you sustain our production environments, build the accelerators and reusable IP that make the next engagement faster, support pre-sales technical discovery, and cross-train on the other platforms so the team stays flexible. These are time-boxed, high-stakes builds. A greenfield foundation goes from zero to a live AI workflow in roughly ten weeks; an acceleration engagement folds hundreds of Clarity tables into an existing lakehouse on weeks-to-months timelines. You'll ship production-grade work in a regulated environment, where "done" means it's governed, documented, and ready to hand to the integration team — not just that the pipeline ran once. Key Responsibilities Work forward-deployed inside the customer's environment: partner directly with their data and IT teams, present design decisions and progress to their technical leadership, and represent QH on-site during kickoffs and key milestones Own platform-specific architecture and build for your stack during active engagements, as technical lead under the Principal Solutions Architect Design and implement ingestion from EHR and source systems (Epic Clarity / Caboodle, FHIR, ERP, scheduling, claims) into a medallion lakehouse Build and harden change-data-capture, transformation, and orchestration pipelines that meet engagement timelines Configure governance, access control, and the data-sharing pattern that hands clean, AI-ready data to QH's platform (Delta Sharing, Fabric External Sharing, Snowflake Reader Accounts, or equivalent) Sustain production environments handed off from prior engagements, and develop reusable accelerators and IP that compress the next build Support pre-sales technical discovery and source-data assessment alongside the Principal SA Ensure every environment meets handoff criteria for the Client Integration team — governed, documented, reproducible Cross-train on the other two platforms to keep the team flexible across single- and multi-engagement states Required Qualifications 8+ years in data engineering or data platform roles, at a Senior or Staff IC level Client-facing maturity — comfortable working on-site in a customer's environment and presenting technical work to their data and IT leadership Deep, hands-on expertise in at least one of Databricks , Snowflake , or Microsoft Fabric (see platform note above) Has shipped production data workloads in a regulated environment (HIPAA, HITRUST, or comparable) Strong in Python and distributed data processing (PySpark or equivalent), plus SQL and modern transformation tooling Comfortable as the sole platform expert on an engagement — you can own a build, not just contribute to one Infrastructure-as-code fluency (Terraform) and CI/CD discipline (GitHub Actions) Pl