Analytics Engineer, Forecasting & Revenue Intelligence

Autodesk•New York, VT

4d•$103,000 - $185,130•Remote

About The Position

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.

Requirements

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

Nice To Haves

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

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