Analytics Engineer, Payer Impact (New York City, hybrid)

Pomelo Care•New York, NY

43d•$150,000 - $190,000•Hybrid

About The Position

Your North Star: Accelerate time to insight by building the foundational data layer that supports analytics across the organization. Trustworthy, actionable data plays a critical role in Pomelo’s mission to improve pregnancy outcomes. We’re looking to bring on an experienced analytics engineer to join the Payer Impact team and help build Pomelo’s data and analytics foundation. As an analytics engineer, you will: Architect and build core data models that power insights that measure the impact of Pomelo programs and enable us to tell our story externally. For example, you may utilize medical claims to define pregnancy episodes, or combine multiple data sources to more reliably link parents to children. Work directly with cross-functional stakeholders and data scientists to understand data needs on the Payer Impact team, and translate requirements into robust data models that enable data scientists and data-savvy stakeholders Identify opportunities to reduce manual time spent on reporting, and implement solutions using the appropriate technical tools Productionize prototype models developed by our healthcare econ team such as cost projection models Advise and partner with data scientists on best practices for building robust, efficient data models in the analytics layer that serve the needs of end users Develop and codify data best practices through documentation, query optimization, self-service tooling, and testing Identify and implement improvements to the quality and reliability of data through data model improvements, better testing, documentation, and self-service tools

Requirements

4+ years professional experience in data science, data engineering, or analytics involving SQL
2+ years professional experience working with healthcare data, and claims data in particular
Experience working in dbt and orchestration platforms like Dagster or Airflow
Experience transforming data using Python
Passionate about transforming raw data into structured tables and analytics deliverables
Excited to work cross-functionally across technical and non-technical stakeholders, including folks who do not share your technical expertise
Strong communication skills and a keen nose for value - someone who can easily and quickly understand the needs of different audiences
Familiar with BI tools (e.g. Looker, Metabase, Tableau) and experience distributing insights to cross-functional teams
Excited to contribute to Pomelo’s mission to improve maternal health outcomes

Responsibilities

Architect and build core data models that power insights that measure the impact of Pomelo programs and enable us to tell our story externally.
Work directly with cross-functional stakeholders and data scientists to understand data needs on the Payer Impact team, and translate requirements into robust data models that enable data scientists and data-savvy stakeholders
Identify opportunities to reduce manual time spent on reporting, and implement solutions using the appropriate technical tools
Productionize prototype models developed by our healthcare econ team such as cost projection models
Advise and partner with data scientists on best practices for building robust, efficient data models in the analytics layer that serve the needs of end users
Develop and codify data best practices through documentation, query optimization, self-service tooling, and testing
Identify and implement improvements to the quality and reliability of data through data model improvements, better testing, documentation, and self-service tools