GTM Engineer

DataSnipper
Amsterdam, Netherlands
Hybrid

Who this role is best for

Geared toward candidates comfortable with building AI-driven GTM systems and collaborating across functions, with a focus on data governance and automation in Amsterdam-based full-time roles.

Best fit for

  • Candidates with experience in building automations and systems within GTM or RevOps functions
    — “People who've spent their growth, marketing, sales, or RevOps careers quietly building automations and tightening the infrastructure underneath their own work”
  • Individuals who have integrated AI and LLMs into their operational workflows
    — “AI fluency you actually use. You've been integrating LLMs, automations, and agents into your work for a while.”
  • Candidates who have worked on CRM data models and data governance practices
    — “Administer and evolve the HubSpot data model: accounts, contacts, deals, and lifecycle stages.”

Things to consider

  • This role requires building from scratch and shaping a new function, which may demand high adaptability and initiative
    — “We are building this function from scratch, and therefore you will have the opportunity to lay out the foundations”
  • Candidates must be comfortable with end-to-end ownership of integrations and vendor tooling
    — “Own GTM tool integrations end to end (Gong, Snowflake, Clay, Default AI, Starbridge, dialers, Common Room, or equivalent)”

How to stand out

  • Highlight experience in shaping systems rather than just executing tasks
    — “You decide how the whole engine is put together, working across every function rather than waiting inside one for requests.”
  • Emphasize hands-on AI integration experience, especially with LLMs and automation tools
    — “Build agents, automations, and AI-assisted workflows in Claude, Default AI, and connected tooling.”
  • Showcase data governance expertise and a track record of enforcing it in workflows
    — “Apply data governance standards: review automation that touches shared CRM objects, and respect change control on the data model.”
  • Demonstrate a history of building and maintaining enrichment workflows
    — “Build and maintain enrichment via Clay and providers such as ZoomInfo, Apollo, Clearbit, and Starbridge.”
  • Position yourself as someone who can translate business needs into technical execution
    — “Work through a request → brief → build → feedback model. Ops people are the interface; they translate field needs into precise briefs you execute against.”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • building and running the GTM and Business Operations stack
  • implementing CRM data model
  • managing integrations and governance
Typical background
experience in RevOpsbackground in growth, marketing, sales, or RevOps

Skills & requirements

Required

CRM Data ArchitectureIntegration ManagementData GovernanceAutomationAI Engineering

Preferred

Enrichment InfrastructureIntent-data InfrastructureData Quality ManagementVendor Tooling

Stack & domain

CRM Data ArchitectureEnrichment And Signal InfrastructureIntegrations And GovernanceAutomations And AI AgentsHubSpotClaySnowflakeGongData GovernanceTAM AnalysisIntent-data InfrastructureData QualitySQLPythonTypeScriptZapierHubspot WorkflowsN8nLovableBoltClaude EnterpriseChatgptSystem BuildingCross-functional CollaborationProcess AutomationInfrastructure GovernanceManual Process To Clean SystemsUngoverned Data To Governed InfrastructureAutomation BuildingInfrastructure TighteningManual Process ImprovementInfrastructure BuildingRevopsICPTerritory ManagementQualified OpportunityCRMAI GTM EngineeringMarketingSalesCustomer SuccessBusiness DevelopmentAIData ArchitectureEnrichmentSignalsIntegrationsToolingGovernanceAI ToolingWorkflow Automation

About the role

Original posting from DataSnipper via Ashby

ABOUT THE ROLE

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.

WHERE THE FUNCTION STANDS TODAY

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.

WHAT YOU WILL BE DOING

CRM & DATA ARCHITECTURE

  • 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.

ENRICHMENT & SIGNALS

  • 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

INTEGRATIONS, TOOLING & GOVERNANCE

  • 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.

AUTOMATION & AI BUILD

  • 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.

ACTIVATE THE BUILD ACROSS EVERY FUNNEL ZONE

  • 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.

PARTNER WITH OPS

  • 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.

WHAT WE'RE LOOKING FOR

The mindset matters more than the title on your CV.

  • 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.
  • AI 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.
  • 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 revenue.
  • Comfort 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 it.
  • A commercial bias. You ask “does this help close a deal?” before “is this elegant?” You measure your work in meetings booked and pipeline influenced.
  • Cross-functional comfort. You can move between marketing, sales, CS, and engineering languages without losing the room.

Tools you'll work with (willingness to ramp matters more than checklist completeness):

  • CRM and data architecture: HubSpot
  • Enrichment and orchestration: Clay, ZoomInfo, Apollo, Clearbit, Starbridge
  • Integrations: Gong, Snowflake, Default AI, dialers, Common Room
  • AI tooling: Claude Enterprise (Projects, Skills, and MCP integrations all unlocked), plus ChatGPT, and a flexible stack. Think: n8n, Lovable, Bolt.
  • Workflow automation: Zapier, HubSpot workflows

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

Source: DataSnipper careers (Ashby)

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