GTM Analytics Engineer

About the role

You will own turning raw, messy GTM data into clean, well-modeled tables that power decision-making across the organization. You will design and build the foundational data infrastructure in BigQuery that supports our entire go-to-market motion from day one. This is a true 0-to-1 role where you set the standards for how data flows from source systems into insights. You will partner closely with sales leadership and RevOps to interpret ambiguous requests and convert them into durable data models. You will become the single trusted person who understands where every number in Hex actually comes from. Your work will directly enable faster resolutions and richer conversations across every customer channel we serve. You will establish the testing and monitoring framework that ensures data quality and trust at scale.

Key facts

What you'll do

• Design and build the foundational GTM data infrastructure in BigQuery, ingesting data from Salesforce, Gong, Outreach, and other GTM systems to form a reliable data lake.
• Write and maintain dbt models that transform raw CRM and sales engagement data into clean, trusted tables for pipeline, forecasting, segmentation, comp, and territory reporting.
• Partner with sales leadership and cross-functional partners to translate ambiguous, ad hoc reporting requests into durable, well-documented data models instead of one-off queries.
• Build and maintain data pipelines that keep GTM data fresh, accurate, and consistent as new tools and data sources are added over time.
• Own data quality end-to-end by establishing testing, validation, and monitoring so the numbers people see in Hex are trustworthy and defensible.
• Set technical standards and best practices for GTM data modeling as the function scales and the data ecosystem grows more complex.
• Create outputs such as dashboards and ad hoc analyses using large datasets in BI tools, with Hex preferred, to enable self-serve analytics across the organization.
• Work directly with RevOps and GTM stakeholders to ensure data definitions are clear, consistent, and aligned with business outcomes.
• Drive infrastructure improvements that reduce manual effort, increase reliability, and support faster decision-making across sales and customer success.
• Identify opportunities to automate data workflows and improve observability so teams can quickly diagnose and resolve data issues.
• Collaborate with engineering partners to integrate new data sources and ensure schemas support efficient querying and downstream consumption.
• Document data structures, pipelines, and logic so that the system is understandable and maintainable by others on the team.
• Contribute to the broader data platform strategy by proposing enhancements that balance speed, quality, and scalability in a high-growth environment.
• Support the Revenue Operations team by providing data-backed insights that inform GTM strategy, forecasting, and resource allocation.
• Participate in on-call or incident response practices for data infrastructure to ensure continuity and reliability for critical reporting.

Requirements

• 4+ years of experience in data or analytics engineering with hands-on ownership of ETL or ELT pipelines in a production environment.
• Strong SQL skills and direct experience building and maintaining data warehouses in BigQuery or a comparable cloud data warehouse.
• Real experience working with GTM data, where Salesforce is a must-have and familiarity with tools like Gong or Outreach is a plus.
• Strong grasp of core SaaS and GTM metrics such as conversion rates, ARR, NRR, win rates, sales cycle length, and quota attainment, and how they are derived from source tool data.
• Comfort turning messy, inconsistent source data into clean, well-organized, documented tables built for downstream reporting and dashboarding.
• Experience creating analytical outputs including dashboards and ad hoc analysis with large datasets in BI tools, with Hex preferred, for self-serve analytics.
• A builder mindset where you are excited to construct foundational data infrastructure from scratch in a fast-moving environment rather than maintain legacy systems.
• Strong cross-functional communication skills that enable you to work directly with sales leadership to clarify needs and translate them into data solutions.

Nice to have

• Experience working in environments backed by venture investors such as a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures.
• Familiarity with our values of Just Get It Done, Invent What Customers Want, Winner's Mindset, and The Polymath Principle and how they shape day-to-day work.
• Exposure to in-office collaboration in a high-velocity, growth-stage company that prioritizes speed and execution.

Practical notes

This role is based in San Francisco and requires in-office presence. The position is full-time and offers standard employment terms consistent with U.S. hiring practices. Applicants should be prepared for a rigorous interview process focused on both technical depth and cross-functional collaboration. No third-party sponsorship is available at this time.