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# Principal Analytics Engineer

- **Company:** adMarketplace, Inc.
- **Location:** New York, NY, United States
- **Salary:** $220,000.0 - $260,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Databases, Data Discovery, Information Engineering, Data Infrastructure, R (Programming Language), Python (Programming Language), Recommender Systems, SQL Databases, Tableau (Software), Usage Analysis, Snowflake, Data Layers, Streamlit Framework, GPT, Databricks
- **Published:** September 21, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=ea56501c0f86b87c

## About the Role

* Exceptional SQL and dimensional/data modeling skills.
 * Experience building production analytical datasets across database systems - Databricks/Snowflake/AWS or equivalent modern data platforms.
 * Experience working with BI/self-service analytics tools such as Sigma, Tableau, or data app solutions like R shiny, Streamlit, ChatGPT Sites.
 * Strong opinions on analytics engineering working models - we want build durable measurement with a focus on immediacy and reproducibility and employ the right tools for the project at hand including dashboards, data-apps, or reusable Python notebooks
 * Ability to translate ambiguous business questions into durable analytical data models.
 * Penchant for writing narratives that explains both the data design architecture of our solutions and the insights they uncover

## Description

As the founding hire for our Analytics Engineering function, you'll have a unique opportunity to build this capability from the ground up including hiring and growing analytics engineers. A core mandate of analytics engineers is to help establish one version of the truth across adMarketplace - reducing reliance on one-off SQL, spreadsheets, conflicting dashboards, and manually maintained reporting. You will actively influence how we define metrics and deep-dive segments, and build data products and semantic foundations around them.

What You'll Do

 * Build the Analytics Data Layer - Build analytics-ready datasets and reusable models for core marketplace concepts; transform raw data into tested, production-quality analytical entities in partnership with Data Engineering.
 * Establish Trusted Metrics - Define and encode canonical metrics with Product, Finance, Measurement, and business teams, and maintain consistent definitions, documentation, and governance.
 * Enable Product Analytics - Create datasets for funnels, cohorts, product adoption, marketplace diagnostics, experimentation, and causal analysis. Help teams understand what changed, where, and why.
 * Scale Self-Service Analytics - Build curated datasets and semantic layers for our BI tools (Sigma, Tableau) and evaluate data app solutions (R Shiny, Streamlit, ChatGPT Sites) to scale automated solutions.
 * Own automation and reproducibility efforts - Automate recurring workflows and apply AI to data discovery, SQL generation, and documentation where useful.


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