Analytics Engineer, GTM

About the Role

As a member of the Data team within the Go-to-Market organization, you will help build a data-driven culture, improve decision-making, and advance strategic initiatives through analytics.

This is a full-stack data role spanning data modeling, metric definition, visualization, analysis, and self-service tooling. You will build trusted, scalable data sources and products that give the business reliable, actionable insights. The work calls for judgment: you will choose the tool, approach, and level of investment that best fit each problem, from a focused analysis to a durable production data product.

As a core partner to the GTM organization, you will address both foundational and ad hoc analytics needs. You will turn complex data into clear narratives that help technical and non-technical audiences understand what is happening, why it matters, and what they should do next.

In This Role, You Will

Partner closely with GTM teams to proactively identify high-impact questions and translate business needs into data models, metrics, analyses, and scalable technical solutions.

Define, source, validate, and operationalize the metrics that guide the business, helping teams incorporate them into planning and day-to-day decisions.

Lead cross-functional data projects across established and emerging business areas, including setting the data strategy for greenfield domains.

Build scalable data models and pipelines that integrate and transform data from multiple sources into trusted, accessible datasets.

Create dashboards, reports, analytical tools, and other data products that enable stakeholders to answer questions independently.

Own the lifecycle of metrics, analytical models, and data products from initial exploration and prototyping through production and ongoing maintenance.

Choose the most effective approach for each problem—whether an analysis, metric, data model, visualization, or self-service product—based on the audience, urgency, complexity, and expected value.

Exercise strong judgment when prioritizing competing requests, balancing immediate business needs with investments that improve the long-term quality and scalability of the data ecosystem.

Use AI-assisted development tools to increase productivity while maintaining clear, tested, and maintainable code, data models, and documentation.

Turn complex findings into clear, persuasive narratives through presentations, written memos, dashboards, and other formats suited to the audience.

You Might Thrive in This Role If You

Have 10+ years of experience in a relevant data role within fast-moving, results-oriented organizations.

Can independently structure and own ambiguous, high-impact business problems from initial framing through recommendation and execution.

Are highly autonomous, resourceful, and creative when navigating technical, operational, and stakeholder constraints.

Exercise strong judgment when deciding what to prioritize, how deeply to invest, and when a quick answer should become a durable data product.

Have deep SQL expertise and extensive experience working with large datasets and designing ETL workflows.

Understand effective software and analytics engineering practices and can use AI tools to move faster without creating brittle systems, unclear code, or unnecessary complexity.

Are proficient in a quantitative programming language, preferably Python.

Have experience with BI tools such as Tableau or Looker and know how to enable effective self-service analytics.