DataSnipper
Demand Generation
GTMEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“GTM Engineer at DataSnipper. Skills: GTM Engineering, Automation, Data analysis, Revenue operations. Partner on the intelligence layer: expand and strengthen the data foundation (enrichment, intent signals, account scoring, ICP detection). Decide which signals matter, how to surface them, and how to route them”
What You'll Achieve.
Measurable lift from AI nurturing agents; Intent signals flow in from across the funnel; Activate intelligence across Sales, Customer Success, Marketing, and Partnerships; Drive specific action through routed signals; Measure adoption and pipeline impact; Largest absolute revenue lever for companies with a sizable user base (lifecycle expansion); Capitalize on conversations after events; Keep quality high at scale (agent governance); Match or beat human version on quality (automated workflows)
Industry & Context.
Identify and eliminate manual work; Replace manual account research, CRM updates, and follow-up drafting with workflows
What They're Looking For.
Must Have
2–4 years in growth marketing, digital marketing, marketing operations, demand generation, RevOps, or a closely adjacent role, AI fluency you actually use, A builder's mentality, A commercial bias, Cross-functional comfort
Nice to Have
Prior GTM Engineering experience is welcome, SQL, Python, TypeScript
What You'll Do.
Partner on the intelligence layer: expand and strengthen the data foundation (enrichment
Decide which signals matter
and how to route them
Co-own the quality of data flowing through HubSpot
Set patterns for new tool and data source integration
Activate signals across the revenue organization: route signals to Sales
and Marketing to drive specific action
and automated handoffs
Understand workflows and bottlenecks of AEs
and Partnership Managers
Measure adoption and pipeline impact
Build programs: stand up signal-based outbound
build lifecycle expansion plays triggered by product signals
orchestrate ABM with multi-channel orchestration
build pre- and post-event automation
Go deeper on localization and agent governance: extend hyper-localization
tighten guardrails on agent behavior
Push automation into adjacent revenue functions: identify and eliminate manual work
automate cross-sell and retention plays
replace manual account research and CRM updates with workflows
How You'll Work.
Team & Collaboration
Partner with the first GTM Engineer on the intelligence layer; Activate intelligence across Sales, Customer Success, Marketing, and Partnerships; Route signals to Sales, CS, Partnerships, and Marketing; Sit with AEs, BDRs, CSMs, and Partnership Managers to understand their workflows; Move between marketing, sales, and engineering languages
Full Job Description
ABOUT THE ROLE We're hiring our second GTM Engineer in the Marketing team in Amsterdam, reporting to the Director of Demand Generation. A year ago, this function didn't exist at DataSnipper. Today our first GTM Engineer has built the foundation. Enrichment runs steadily. AI nurturing agents are live and lifting reply rates. Intent signals flow in from across the funnel. The function has reached a turning point: we collect rich intelligence that still lives inside Demand Generation, and there's a list of programs we haven't built yet (Intent signal orchestration, ABM, event automation, deeper hyper-localization). We need an operator who finds manual process offensive. Someone who's been quietly building automations inside their growth or marketing job because they couldn't stand the inefficiency. Someone ready to do this full-time, with a function that already has shape and runway. You'll partner with the first GTM Engineer on the intelligence layer (signals, enrichment, intent data, ICP detection) and own the work of activating that intelligence across Sales, Customer Success, Marketing, and Partnerships. WHERE THE FUNCTION STANDS TODAY We've run GTM Engineering as a discipline for about a year. Enrichment flows steadily across inbound and target accounts. AI nurturing agents produce measurable lift. We collect rich intent data across the funnel, and most of that intelligence still lives inside Demand Generation rather than serving the wider revenue organization. Hyper-localization works unevenly. Our agents sometimes switch into the local language on their own, and we don't always catch when that's a win or a loss. Programs we haven't built yet include the ABM with multi-channel orchestration, pre- and post-event automation, deeper signal surfacing into Sales and CS and Partnerships, and more automated workflows in adjacent revenue functions. The second hire is for activating what we have and building what we don't. WHAT YOU WILL BE DOING PARTNER ON THE INTELLIGENC
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