Forward Deployed Analytics Engineer

Translucent

$150K — $200K *
Healthcare
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of relevant industry experience in healthcare data analytics or health tech.
  • Strong SQL proficiency, with bonus experience in BigQuery SQL dialect.
  • Hands-on familiarity with modern data platforms such as Databricks or Snowflake.
  • Experience with transformation tooling, especially dbt-style workflows.
  • Solid understanding of data modeling and pipeline architecture.
  • Ability to reverse-engineer complex business logic from under-documented systems.
  • Basic proficiency in Python and experience with git workflows.

Responsibilities

  • Understand and document customer requirements, processes, and business logic.
  • Identify necessary data for customer workspace and review source-of-truth models.
  • Reverse-engineer customer-specific business rules and data transformations.
  • Build and validate SQL transformations to align with the company's unified ontology.
  • Ensure testing and validation rigor across all data transformations.
  • Collaborate with the data platforming team to address pipeline or platform constraints.
  • Engage directly with customers to validate data access and understand their systems.

Benefits

  • In-office work 4 days per week in Union Square, New York City.
  • Opportunities for collaboration with product and engineering teams.
  • High-ownership role with direct customer engagement.
  • Exposure to various modern data platforms and transformation tools.
  • Potential for professional development in advanced healthcare data standards.
Full Job Description
About the role

We're hiring a Forward Deployed Analytics Engineer to join our team in New York. You will sit at the intersection of our customers' financial and clinical data and the agentic AI systems we are building on top of it. Working within our managed data pipeline, you will reverse-engineer customer-specific business rules, build the transformations that map raw customer data into our unified ontology and semantic layer, and hold the bar for correctness on everything that flows through it.

This is a high-ownership role. You will work directly with customers to understand their source-of-truth financial and clinical models, then translate that understanding into durable, well-tested data transformations.
What you'll do
  • 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
Must-haves
  • 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.
Nice-to-haves
  • 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
Education

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.
Location

Union Square, New York City. In-office 4 days per week.
Compensation

$150k - $200k

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