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# Forward Deployed Analytics Engineer

- **Company:** Wintermeyer Ventures
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $150,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Business Logic, Clinical Data Repository, Encodings, Customer Data Management, Data Transformation, Database Queries, Python (Programming Language), SQL Databases, Application Enhancement Tool, Model Validation, Data Pipelines
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/forward-deployed-analytics-engineer-new-york-ny--f09d643e-5daa-472a-8a13-0b0780f09e98

## About the Role

Team Building, Artificial Intelligence (AI), Clinical Data, Healthcare, Finance, Customer/Client Research, Data Modeling, Model Review, Reimbursement, SQL (Structured Query Language), * At least 5 years of experience in data or analytics engineering.

 * Strong SQL skills and experience with Python, data transformation tools, and modern data pipelines.
 * Hands-on healthcare data experience in claims, reimbursement, provider revenue cycle, or health system finance, in addition to any clinical or EHR experience.
 * Experience authoring and owning SQL or dbt transformation models that encode healthcare business logic.
 * Experience designing and shipping a data pipeline or platform end to end, along with customer-facing technical work such as integrations, solutions engineering, or forward-deployed work.
 * A bachelor's degree or higher in a quantitative or business-adjacent field, or equivalent hands-on healthcare data experience.
 * Background in a fast-paced healthtech, health system, or healthcare consulting environment.
 * Authorization to work in the United States without visa sponsorship.

## Description

Join a healthtech team building AI-powered tools for healthcare finance. You will translate customer financial and clinical data into reliable transformations and a shared semantic layer, helping ensure the platform's insights are accurate and trusted., * Review customer data models and work with finance and clinical teams to understand their source-of-truth logic.

 * Turn under-documented payer contract, claims, reimbursement, and chart-of-accounts rules into durable, tested SQL transformations.
 * Map customer data into a unified ontology and semantic layer within managed data pipelines.
 * Own testing and validation to maintain a high standard of correctness.
 * Collaborate with insights and product engineering teams to extend the ontology for new customer needs and data sources.