Senior Forward Deployed Data Engineer, Data Modernizaton

Qualified Health PBC

3d•$180,000 - $230,000•Hybrid

About The Position

Qualified Health is 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 an opportunity to build the future of AI in healthcare, solve complex challenges, and make a lasting impact on patient care. Data Modernization is a forward-deployed function where every role 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. 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. 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.

Requirements

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
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)

Nice To Haves

Databricks: Delta Lake, Unity Catalog, Delta Sharing, Delta Live Tables, Photon. Bonus: production Databricks experience inside a health system or Databricks partner consultancy.
Snowflake: Snowpark, Reader Accounts, Streams & Tasks, Dynamic Tables, Snowpipe, strong dbt fluency. Bonus: Epic Clarity inside Snowflake.
Microsoft Fabric: OneLake, SQL Server Mirroring for CDC, Fabric Data Factory, Fabric External Sharing, Iceberg shortcuts. Bonus: prior Azure Synapse / ADF / Databricks-on-Azure background.
Resident / customer-success solutions architect or engineer from a cloud data platform vendor (Databricks, Snowflake, Microsoft FastTrack / CSU)
Senior data engineer from a health system running on your platform, or from a platform-partner consultancy
Familiarity with EHR data models and the realities of on-prem-to-cloud CDC
Background in consulting, professional services, or data platform implementation in regulated industries (healthcare strongly preferred; fintech a strong adjacent)
Ownership: You're the one person on the engagement who deeply knows this platform, and you carry that weight without needing a second set of hands on every decision.
Pragmatism: You know the difference between architecturally ideal and deliverable-in-ten-weeks, and you optimize for the latter without creating technical debt.
Reusability mindset: You build the second engagement's accelerator while delivering the first, because you've felt the cost of bespoke-everything.
Clinical-data literacy: Clarity and Caboodle don't scare you; you understand why health system data is messy and you've untangled it before.
Cross-platform curiosity: Your depth is in one stack, but you're glad to learn the other two so the team can flex across engagements.

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