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GTM Engineer

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: Blink - The Employee App
Part Time position
Listed on 2026-06-07
Job specializations:
  • IT/Tech
    Data Engineer, Data Analyst
Salary/Wage Range or Industry Benchmark: 60000 - 80000 GBP Yearly GBP 60000.00 80000.00 YEAR
Job Description & How to Apply Below
Location: Greater London

London (Old Street, 3 days/week)

Reports to:
Director of Revenue Operations

We're not just closing the digital divide; we're reconnecting distributed organisations, enabling seamless communication, and re-engaging employees like never before. Blink, a mobile-first employee experience platform, puts everything employees need right in their hands. With teams in Boston, London, and Sydney, we're making waves worldwide, partnering with industry leaders like Domino's, JD Sports and McDonald's.

The Role

As a GTM Engineer, you will play a pivotal role in shaping Blink's go-to-market operations, ensuring our systems are robust, scalable, and data-driven. We're building a small, high-output revenue operations team, and this is a key hire. You'll report to the Director of Revenue Operations and work across the full scope of the function: sales ops, marketing ops, and CS ops.

We're looking for a GTM engineer who can build the systems that turn signals into pipeline. But this isn't a pure build-and-ship role. You'll sit close enough to the business to understand why something needs building in the first place. That means understanding how our sales, marketing, and CS teams work, where the friction is, and what's actually going to move the number.

Some weeks that's architecting a new automation. Other weeks it's digging into a process that isn't working and figuring out the fix.

This role owns the automation, enrichment, and integration layer that connects our go-to-market tools and makes them smarter over time. You won't just maintain what exists. You'll spot where manual work is slowing us down, where data isn't flowing where it should, and where AI can do in seconds what currently takes hours. Then you'll build the fix, measure the impact, and move on to the next one.

Key responsibilities:

AI-powered automation and pipeline generation (70%)

  • Build and maintain AI-powered workflows for prospect enrichment, research, and outbound personalization using tools like n8n and Claude
  • Own the intent-to-pipeline lifecycle end to end: configure signals, define scoring and routing logic, get the right leads to the right people at the right time, and iterate based on what converts
  • Own our partnership data pipeline, making sure overlap data flows into Hub Spot cleanly and drives action
  • Identify and MVP-test new pipeline sources. New tools, new signals, new channels, new automations. If it could generate pipeline, you'll try it
  • Own data pipelines from Snowflake into our other tools, keeping customer and prospect data continuously enriched and actionable

Hub Spot and marketing/CS automation (30%)

  • Own core Hub Spot automation: lead routing, lifecycle workflows, deal stage triggers, property hygiene
  • Provide technical support for marketing and CS automation, including complex nurture logic, custom integrations, and attribution
  • Maintain data quality across the GTM stack: deduplication, field standardisation, and automated hygiene rules
Who you are:
  • Above all, you figure things out. You won't know every tool on day one. What matters is that when you hit something new, you go and learn it
  • 2-4 years in marketing ops, sales ops, or revenue ops, ideally in a B2B SaaS environment
  • Comfortable building automations and integrations. You've worked with APIs, webhooks, and workflow tools like n8n, Zapier, Tray, or similar, and you'd rather build something than do it manually twice
  • Hands‑on with Hub Spot. You know workflows, custom properties, and how to make the CRM do what the business actually needs
  • Actively experimenting with AI in GTM workflows. You don't just know the buzzwords. You've actually built things with LLMs, prompt engineering, or AI‑assisted tooling and can show what you've shipped
  • Comfortable with data. You can write SQL, work with Snowflake, and debug a broken pipeline without waiting for someone else to fix it
  • You think in systems, not tasks. When you see a request, you ask whether this should be automated, what else it connects to, and how it should scale
  • A clear communicator who can work with salespeople, marketers, and CS without making everything sound like an engineering ticket
Preferred Qualifications:
  • Experience working in a B2B…
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