Analytics Engineer, Forecasting & Revenue Intelligence

Position Overview

Autodesk’s worldwide sales organization depends on its forecast, pipeline, targets and reporting. This role builds the data models behind them. As an Analytics Engineer on the Forecasting & Revenue Intelligence team, you turn sales, subscription and hierarchy data into tested, documented models that analysts and sales leaders can trust, covering what customers bought, who owns which accounts and how the sales organization looked on any given date. You will work in SQL and dbt on Snowflake, and you will work closely with the people who use your models. This is a hands-on role on a new team, and you will own what you ship.

Location: United States (remote). Central or Eastern time zone preferred.

Organization: Revenue Operations

Responsibilities

• Build and maintain dbt models on Snowflake that bring Salesforce, subscription, billing, hierarchy and forecast data into a clean, documented form
• Model data for analysis: a clear grain, stable keys, and definitions consistent with the shared metric dictionary
• Keep history so any published number can be reproduced as it stood on the day it went out
• Maintain the mapping between accounts, territories, sellers and the sales hierarchy as the organization changes
• Reconcile the data to Salesforce and to Finance, and find the cause when they disagree
• Build the datasets behind the weekly forecast pack, business reviews and leadership dashboards
• Add tests and monitoring for freshness, completeness and accuracy, and fix what breaks
• Explain data issues and trade-offs to sales and finance partners in plain terms, and agree on a fix with them
• Work in version control with code review and continuous integration

Minimum Qualifications

• Bachelor’s degree in a technical or quantitative field, or equivalent practical experience
• 3+ years in analytics engineering, data engineering or BI development, building models other people depended on
• Dbt in production, with tests and documentation as part of how you work
• Strong SQL, including window functions and incremental models, in a cloud data warehouse such as Snowflake
• Working knowledge of the Salesforce data model: accounts, opportunities, line items and ownership
• Ability to explain a data problem to a non-technical stakeholder and reach a decision together

Preferred Qualifications

• Dbt snapshots or slowly changing dimensions for point-in-time reporting
• Python for transformation or orchestration, with Airflow or similar
• Enterprise software or SaaS commercial data: subscriptions, renewals, territories, and direct and partner routes to market
• Revenue intelligence platforms such as Clari, Gong or Aviso, and BI tools such as Power BI, Tableau or Sigma
• Experience as an early hire on a new data team