About the Role
The Revenue Operations team at Gusto is a full-stack team responsible for data, analytics, and operational excellence in pursuit of scaling our revenue growth. The Go-To-Market Analytics team is one functional area, responsible for defining and owning the metrics for scaling our Sales teams.
Gusto is looking for a Revenue Analytics Engineer to build and maintain foundational data infrastructure that is crucial to growing and scaling our Sales efforts. In this role, you will partner with our GTM analysts to scope and deliver data products for an audience ranging from company and revenue leadership to operational and frontline sales. In doing so, you will own significant portions of our sales data from end-to-end, focusing on the transformation, design, and visualization workflows. In addition, you will establish best practices for systems design and workflows to maximize usefulness of AI at scale.
This role will report to the Head of Go-To-Market analytics, and partner closely with Data Science, Data Platform, and Business Technology teams.
Day-to-Day Responsibilities
Establish relationships with internal stakeholders to determine business needs, scoping and delivering solutions through data products.
Design, build, and maintain data pipelines and dashboards to automate "keep the lights on" work out of manually-managed processes.
Build a data foundation by incorporating business logic into raw data tables, laying the groundwork to enable value-add insights.
Create a dynamic reporting environment based on stakeholder needs.
Identify data discrepancies and set best practices for data logic to create a clean and well-documented environment.
Collaborate with broader data organization as steward to the definition and process management of core Gusto metrics.
Requirements
Education or work experience in Engineering or Computer Science, or a related technical field
7+ years of experience in an analytics engineering, business intelligence, or technical data analytics role
Experience with SQL and ETL optimization techniques, especially within cloud-based data warehouses like Redshift, Snowflake, etc.
Command-line experience and familiarity with version control collaboration tools (git)
Experience with data pipeline management technologies with dependency checking, such as Airflow, as well as schema design and data modeling tools (dbt)
Experience with data visualization technologies, e.g., Tableau, Looker, Sigma, Mode, Hex
Experience with Python and data ingestion tools
Ability to problem-solve open-ended problems and project manage dependencies and timelines to optimal outcomes
Ability to demonstrate tools, business intuition, and attention to detail for data validation and QA
Compensation
Our cash compensation amount for this role is targeted at $138,000-156,000 in Denver & most remote locations, and $168,000-189,000 in New York & San Francisco Bay Area. Stock equity is additional. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.