The GTM Data & Attribution Engineer at Oneleet will own the data backbone of our go-to-market motion, from first ad click to closed-won deal. You’ll work alongside our GTM Engineer, and you will have a deep focus on synthesizing funnel insights between marketing and sales. You will be responsible for gathering, analyzing, interpreting, and visualizing all of our marketing and sales data.
You will build and maintain the pipeline that pulls data from HubSpot, Dreamdata, Google Ads, LinkedIn, PostHog, and our website into BigQuery as a single, trustworthy source of truth. You will be the person who can explain, with certainty, why HubSpot says one number and Google Ads says another, and which one to believe. You will turn that clean data into dashboards executives actually use, and into account intelligence that makes our ABM and outbound motions sharper.
You will thrive here if you get genuinely excited building motions from scratch, about reconciling conflicting numbers across platforms, if you understand browsers and tracking well enough to explain why the discrepancy exists, and if you’d rather build a pipeline once, correctly, than patch the same spreadsheet every week.
Data gathering & Pipeline Ownership: Design, build, and manage our data pipeline in BigQuery, unifying data from HubSpot, Dreamdata, Google Ads, LinkedIn, PostHog, and the website into one reliable source of truth. Document the pipeline so it scales beyond you and survives tool changes.
Attribution & Tracking: Maintain deep, working knowledge of how browsers work, how data is sent, and how cookies, JavaScript, and (server-side) GTM are used. Investigate and resolve discrepancies between platforms and explain why to stakeholders, not just report the gap.
Dreamdata & Revenue Attribution: Configure and continuously refine Dreamdata to model the full prospect journey, anonymous visitor to closed-won. Use Dreamdata to determine which channels and campaigns are actually generating pipeline. Partner with sales and marketing to translate Dreamdata insights into budget and channel decisions.
Visualization & Reporting: Build and maintain a clear, executive-facing dashboard (Looker/Looker Studio) showing the performance by channel: spend, leads, meetings, pipeline, and closed-won. Ensure dashboards answer “where is revenue actually coming from?” at a glance, with the ability to drill into any channel or campaign. Keep reporting logic consistent with the underlying attribution model so numbers don’t silently diverge.
ABM with Clay & AI: Design and run an ABM strategy grounded in our ICP, using Clay to enrich and score accounts, layering in firmographic, intent, and behavioral signals. Leverage AI to personalize messaging at scale in a way that actually gets replies.
General:
5+ years in GTM operations, revenue operations, marketing operations, or analytics engineering at a B2B SaaS company, with hands-on ownership of marketing/sales data infrastructure.
Scientific mindset of experimentation, creating and testing hypotheses.
Love of working on new platforms that help automate and enhance channel performance.
Knowledge of how to simplify and act on findings.
Technical:
Strong SQL skills and hands-on experience building and maintaining pipelines in BigQuery (or a comparable warehouse).
Deep understanding of how browsers, cookies, JavaScript, and tracking pixels work. Able to diagnose why numbers differ across platforms, not just flag that they do.
Hands-on experience with Google Tag Manager , including server-side GTM and data layer configuration.
Experience with Dreamdata or a comparable B2B attribution platform (Bizible, HubSpot Attribution, etc.).
Hands-on HubSpot experience (CRM, Marketing Hub, Operations Hub): workflows, custom objects, data sync.
BI tool proficiency (Looker / Looker Studio, Tableau, or similar). Building dashboards, not just reading them.
Working knowledge of APIs, webhooks, and data integration patterns across platforms not designed to talk to each other.
Strategic:
Deep understanding of B2B SaaS funnels, buyer journeys, and revenue metrics ( MQL, SQL, pipeline, win rate, CAC, LTV ).
Experience designing and implementing UTM strategies and multi-touch attribution models.
Understanding of ABM fundamentals : ICP definition, account scoring, and personalized outbound at scale.
Cross-functional communication skills. Able to explain a tracking discrepancy to a sales rep and an attribution model to a CEO with equal clarity.
Experience at an early-stage startup as the first or only data/ops hire.
Experience with Clay (workflows, enrichment, AI columns, Claygent).
Python scripting for data manipulation and automation.
Experience with PostHog or similar product analytics tools.
Familiarity with reverse ETL tooling and broader data warehousing concepts.
HubSpot certifications (Revenue Operations, Marketing Hub, Operations Hub).
Google Ads campaign management and conversion optimization experience.
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