Forward Deployed Analytics Engineer

• Understand customer requirements, current processes, workflows and business logic.
• Identify the data required to stand up a customer workspace, and review customer source-of-truth financial and clinical data models — potentially on-site with customers to capture business logic firsthand.
• Reverse-engineer and codify customer-specific business rules, from payer contract logic to chart-of-accounts idiosyncrasies.
• Build and validate transformations that map customer data into Translucent's unified ontology and semantic layer, using SQL within our managed data pipeline.
• Own testing and validation rigor for every transformation you ship — you are the last line of defense on data correctness.
• Partner with our data platforming team when transformation needs surface pipeline or platform constraints, without owning that infrastructure yourself.
• Interact directly with customers to confirm data access and validate your understanding of their source systems and business logic.
• Work with our platform team to identify expansion opportunities for core infrastructure and shared services, based on patterns you see across customer engagements.
• Partner with our insights and product engineering teams to understand and expand our data ontology as new customer needs and data sources emerge.

What we're looking for

• Deep healthcare data domain experience — prior work at a health system, healthcare-focused consulting, or health tech, with hands-on exposure to claims, EHR, or financial/revenue cycle data.
• Comfort reverse-engineering messy or under-documented business logic directly from source systems.
• Strong SQL — this is the primary tool of the role, and we expect real fluency, not familiarity. Bonus points for BigQuery SQL experience.
• Experience working inside a modern data platform (Databricks, Snowflake, Fabric, BigQuery, or similar) as a hands-on user.
• Experience with dbt-style transformation tooling (we use SQLMesh) including model contracts and layered/medallion architectures; comfort working in transformation-as-code workflows including testing and validation.
• Solid data modeling and pipeline instincts: comfortable reasoning about schemas, normalization vs. denormalization, modeling complex domain entities and operating a data pipeline.
• Comfortable operating in a git-native, PR-driven workflow with basic Python — version control, code review, and shipping changes through an established CI/CD pipeline.
• 3-5+ years of relevant industry experience.

• Epic Cogito and Epic Clarity certifications or accreditations
• Comfort working under strict PHI/data-governance constraints (e.g., synthetic-only test fixtures, no real patient data in code).
• Healthcare interoperability standards experience (HL7, FHIR, X12 837/835).
• Experience working directly with customers or stakeholders in a forward-deployed, integrations, or solutions engineering capacity.
• Hands-on experience with GCP BigQuery SQL dialect

Bachelor's degree (or higher) in a quantitative or business-adjacent discipline — computer science, statistics, mathematics, health informatics, or finance/accounting — or equivalent experience in healthcare data, revenue cycle, or health system finance.

We weigh hands-on healthcare data experience and SQL fluency at least as heavily as formal degree background.

Union Square, New York City.

In-office 4 days per week.

$150k - $200k