Decagon Logo

Decagon

GTM Analytics Engineer

Posted One Month Ago
In-Office
San Francisco, CA, USA
190K-230K Annually
Mid level
In-Office
San Francisco, CA, USA
190K-230K Annually
Mid level
Design and build GTM data infrastructure in BigQuery, ingesting and modeling Salesforce and other GTM sources. Create durable dbt models and pipelines, ensure data quality with testing and monitoring, partner with sales leadership to translate requests into trusted tables, and produce dashboards and analyses for forecasting, pipeline, segmentation, comp, and territory reporting.
The summary above was generated by AI

About Decagon

Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.

Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.

We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.

We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.

About the Team

Decagon’s Revenue Operations team is a multidisciplinary group of operators combining strategic thinking, analytical rigor, and high-velocity execution. Covering GTM-wide strategy, operations and analytics, we are proactive, data-driven partners to leadership – providing critical insights, driving operational efficiency, and getting things done.

About the Role

Decagon is looking for its first GTM Analytics Engineer to build the data infrastructure that our entire go-to-market organization runs on. You'll own turning that raw, messy data into clean, well-modeled tables that the rest of RevOps, sales leadership, and the exec team can actually build on. This is a true 0-to-1 role with support from the broader RevOps & GTM team: you'll design lots of data structures and modeling layers from the ground up, set the standards for how GTM data gets structured, and become the trusted person to answer "where does this number actually come from."

In this role, you will

  • Design and build the foundational GTM data infrastructure in BigQuery — ingesting, organizing, and modeling data from Salesforce, Gong, Outreach, and other GTM systems into a reliable data lake

  • Write and maintain models that transform raw CRM and GTM tool 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 rather than one-off queries

  • Build and maintain data pipelines that keep GTM data fresh, accurate, and consistent as new tools and data sources get added

  • Own data quality end-to-end — establishing testing, validation, and monitoring so the numbers in Hex are numbers people trust

  • Set technical standards and best practices for GTM data modeling as the function scales

Your background looks something like this

  • 4+ years of experience in data/analytics engineering, with hands-on ownership of ETL/ELT pipelines and dbt in a production environment

  • Strong SQL skills and direct experience building and maintaining data warehouses in BigQuery (or a comparable cloud warehouse)

  • Real experience working with GTM data — Salesforce is a must, plus familiarity with tools like Gong, Outreach, or similar sales engagement platforms in a high-growth B2B company is a plus

  • Strong grasp of core SaaS and GTM metrics — conversion rates, ARR/NRR, win rates, sales cycle length, quota attainment — and how they're derived from the underlying GTM tool data

  • Comfort turning messy, inconsistent source data into clean, well-organized, documented tables built for downstream reporting and dashboarding

  • Experience creating outputs, including dashboards, ad hoc analysis with large datasets in BI tools (Hex preferred) for dashboarding and self-serve analytics

  • A builder mindset — you're excited to build foundational infrastructure from scratch in a fast-moving environment rather than maintain an existing system

  • Strong cross-functional communication skills; you can work directly with sales leadership to understand what they actually need, not just what they ask for

Benefits

We proudly offer the following benefits for our full-time employees:

  • Medical, Dental, and Vision benefits for you and your family

  • Life Insurance and Disability Benefits

  • Retirement Plan (e.g., 401K, pension)

  • Parental Leave

  • Fertility and family building benefits through Carrot

  • Monthly stipend to support your wellness, lifestyle, and work-life balance

  • Daily lunches and snacks in the office to keep you at your best

  • Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)

These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.

Similar Jobs

22 Days Ago
Hybrid
San Francisco, CA, USA
220K-335K Annually
Expert/Leader
220K-335K Annually
Expert/Leader
Artificial Intelligence • Machine Learning • Generative AI
Build scalable data models, pipelines, metrics, dashboards, analytical tools, and self-service data products for Go-to-Market teams. Partner with stakeholders to solve ambiguous business problems, establish data strategies, operationalize trusted metrics, and communicate insights through persuasive narratives. Own data products from exploration through production and maintenance, balancing immediate needs with long-term scalability while applying strong analytics engineering practices and AI-assisted development tools.
Top Skills: ETLLookerPlotly DashPythonReactSQLStreamlitTableau
20 Minutes Ago
Hybrid
23-31 Hourly
Junior
23-31 Hourly
Junior
Fintech • Financial Services
Build customer relationships in a bank branch by understanding financial needs, recommending products and services, supporting account openings and credit applications, handling cash and teller transactions, using digital banking tools, and making referrals to specialists. The role requires compliant service, risk awareness, proactive outreach, collaboration, and Saturday availability.
20 Minutes Ago
Hybrid
23-31 Hourly
Junior
23-31 Hourly
Junior
Fintech • Financial Services
Build customer relationships in a branch setting by identifying financial needs, recommending banking products and services, opening accounts, processing transactions, supporting credit applications, and making referrals. The role combines customer service, sales growth, cash handling, digital banking assistance, compliance, risk awareness, and collaboration with branch teammates. Saturday availability and SAFE registration are required.

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account