GTM Engineer

Datasnipper; Netherlands; Hybrid; EUR 70,000 - 100,000; Full time

Job summary

Datasnipper is seeking a GTM Engineer to build and run the Data, Systems & AI Engineering layer beneath the GTM and Business Operations stack.

You will own the CRM data architecture, build the enrichment and signal infrastructure, run integrations and governance holding the wider stack together (Clay, Snowflake, Gong, and more), and build automations and AI agents used daily by Marketing, Sales, CS, and BD.

Qualifications

• 2–4 years in RevOps, marketing/sales/CS operations, data/CRM administration.
• Prior GTM Engineering experience is a plus.
• Bonus: SQL, Python, or TypeScript.

Responsibilities

• Own GTM tool integrations end to end.
• Build data model and governance across CRM.
• Develop enrichment and signals with Clay, ZoomInfo, Apollo, Clearbit.
• Shape vendor and tool decisions to consolidate tools.
• Develop TAM analysis and intent-data infrastructure.
• Build AI-assisted workflows and agents.

Skills

RevOps

Marketing ops

Sales ops

Data/CRM administration

HubSpot

GTM engineering

SQL

Python

TypeScript

Tools

HubSpot

Job description

• We're hiring a GTM Engineer to build and run the Data, Systems & AI Engineering layer underneath DataSnipper's GTM and Business Operations stack
• This is the build function: if RevOps decides what the ICP is, who owns which territory, and what counts as a qualified opportunity, this team turns those decisions into the systems that actually run them
• That's a bigger remit than any one tool
• You'll own the CRM data architecture, build the enrichment and signal infrastructure that feeds it, run the integrations and governance holding the wider stack together (Clay, Snowflake, Gong, and more), and build the automations and AI agents that turn all of it into something Marketing, Sales, CS, and BD run on every day
• You decide how the whole engine is put together, working across every function rather than waiting inside one for requests
• We are building this function from scratch, and therefore you will have the opportunity to lay out the foundations of what a world class AI GTM Engineering team can look like in a fast paced AI company
• We are looking for a team that can take and build upon the existing state- Marketing has built real foundation where enrichment runs steadily, AI nurturing agents are live and lifting reply rates, intent signals flow in from across the funnel, and HubSpot is trusted as the data model of record for accounts, contacts, deals, and lifecycle stages
• This team will be building the next next frontier: own integrations and vendor tooling (Gong, Snowflake, Clay, Default AI, Common Room, dialers) end to end instead of managing them reactively, and turn data governance - who can touch shared CRM objects, what change control looks like - from a principle into enforced practice
• Beyond that, there's a funnel zone each for Sales, CS, and BD still waiting to be built out, on top of the intelligence Marketing already relies on
• We need operators who are instinctively drawn to turning manual process into clean systems, and ungoverned data into governed infrastructure
• People who've spent their growth, marketing, sales, or RevOps careers quietly building automations and tightening the infrastructure underneath their own work, and are ready to do both full-time inside a function that already has shape and runway
• Administer and evolve the HubSpot data model: accounts, contacts, deals, and lifecycle stages
• Implement lead routing, ICP, and territory logic into the CRM per rules RevOps defines - you build it, RevOps owns what it means
• Implement rules of engagement (ROE) - handoff criteria and account rules - into CRM workflows, automation, and Clay infrastructure that execute them reliably
• Build and maintain enrichment via Clay and providers such as ZoomInfo, Apollo, Clearbit, and Starbridge
• Run TAM analysis and intent-data infrastructure, and keep data quality high through continuous enrichment workflows
• Decide which signals matter, how to surface them, and how to route them to the people who should act on them
• Be the mirror and advisor to the business teams through your work
• Own GTM tool integrations end to end (Gong, Snowflake, Clay, Default AI, Starbridge, dialers, Common Room, or equivalent) so data flows cleanly with no duplicate or conflicting records
• Apply data governance standards: review automation that touches shared CRM objects, and respect change control on the data model
• Shape vendor and tool decisions - fit, overlap, integration complexity - so we consolidate instead of running five tools for one job
• Build and maintain the core Clay & Lemlist infrastructure: account data, enrichment, sequences, templates, and how contacts flow in and out
• Develop account scoring models and standardized Clay functions that Sales and Marketing can use without building their own underlying workflows
• Build agents, automations, and AI-assisted workflows in Claude, Default AI, and connected tooling
• Marketing (inbound signal MQL): inbound enrichment and routing, audience activation, intent signal infrastructure. Drive signal-based outbound - detect a buying moment (hiring, funding, leadership change, product usage shift), find the decision-maker, enrich, send
• Sales (SQL Closed Won Renewal Expansion): prospecting automation, account planning tooling, rep efficiency. Build lifecycle expansion plays triggered by product signals so CS and AEs get prompted when an account is ready to expand
• BD (outbound signal partner + BD pipeline): partner signal workflows, account intelligence, BD-specific outreach and pipeline automation
• CS (Closed Won Adoption Health): onboarding automation, health-score workflows, renewal and expansion signal tooling
• Work through a request brief build feedback model. Ops people are the interface; they translate field needs into precise briefs you execute against
• Functions consume what you build rather than configuring or building it themselves, and feedback routes back through Ops - keeping your time focused on builds, not ad-hoc asks or slides

A builder's mentality. When you hit a wall, you build the thing rather than file a ticket. You pick up Lovable, Bolt, n8n, or whatever new tool surfaces. You've shipped automations that touched real revenueComfort owning infrastructure, not just automations. You own a data model, an integration, or a governance rule as confidently as you own the plumbing - not just what sits on top of itAI fluency you actually use. You've been integrating LLMs, automations, and agents into your work for a while. You can talk concretely about what works, what breaks, and what's still a hack

Integrations: Gong, Snowflake, Default AI, dialers, Common Room

2-4 years in RevOps, marketing/sales/CS operations, data/CRM administration, or a closely adjacent role. Prior GTM Engineering experience is a plus, not a requirement - the strongest people in this discipline today are crossovers

CRM and data architecture: HubSpot

Bonus: SQL, Python, or TypeScript. The real signal is willingness to learn by tinkering

AI tooling: Claude Enterprise (Projects, Skills, and MCP integrations all unlocked), plus ChatGPT, and a flexible stack. Think: n8n, Lovable, BoltWorkflow automation: Zapier, HubSpot workflowsEnrichment and orchestration: Clay, ZoomInfo, Apollo, Clearbit, StarbridgeCross-functional comfort. You can move between marketing, sales, CS, and engineering languages without losing the room