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# Analytics Engineer

- **Company:** Paramount Pictures
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $85,600.0 - $128,400.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, BigQuery, Information Engineering, Python (Programming Language), SQL Databases, Google Cloud, Data Pipelines
- **Published:** October 26, 2026
- **Apply:** https://careers.paramount.com/talentcommunity/apply/1443286200/?locale=en_US

## About the Role

* 2+ years of experience in data engineering, business intelligence, data science, or analytics.
 * Ability to break complex problems into simple, coherent solutions.
 * Extensive experience writing robust Python and SQL as part of a team.
 * Robust attention to detail and commitment to data accuracy.
 * Ability to communicate concisely and persuasively with nontechnical stakeholders.
 * Successful completion of a background check.

Bonus Skills (Nice-to-Haves)

 * Experience integrating AI solutions into existing business processes.
 * Experience with media or subscription businesses.
 * Experience using Google Cloud Platform, including BigQuery, ML Engine, and APIs.

## Description

Paramount, a Skydance Corporation, creates entertainment experiences that connect audiences around the world. Within the Data & Insight Group, you'll support our global direct to consumer (DTC) business as an Analytics Engineer. This Journey IC role is part of the Data Engineering job family and is based in Los Angeles, CA, or New York, NY.
You'll own global DTC subscriber forecasts, using models built by the data science team to inform important business decisions. You'll partner with stakeholders to understand the business, build data pipelines upstream and downstream of models, and diagnose variance against forecasts. Success requires close attention to detail, clear and influential communication, and ownership in a fast moving environment.
Responsibilities

 * Partner with stakeholders to understand their needs and the DTC business.
 * Collaborate with data science to understand forecasting models and with data engineering to understand the data underlying models and forecasts.
 * Create global DTC subscriber forecasts for regular business processes and strategic requests as they arise.
 * Build data pipelines upstream and downstream of forecasting models, including forecast reporting pipelines.
 * Diagnose variance against forecasts and communicate findings clearly, concisely, and convincingly to stakeholders.
 * Partner with dashboard engineers to build and improve the forecast dashboarding environment for stakeholders and practitioners.
 * Estimate the effects of important business decisions through subscriber forecasting.