GTM Engineer
The role
We are looking for a hybrid, highly technical GTM Engineer to bridge the gap between marketing technology, revenue operations, and software engineering. In this role, you won't just be configuring tools, you will be architecting, automating, and maintaining the engine that powers our revenue ecosystem, working alongside your Engineering & Operations peers.
Your primary focus will be on our Marketing Technology (MarTech) ecosystem including advanced marketing automation, lead management architecture, and AI driven enrichment pipelines. As a core member of our Revenue Systems team, you will have full remit across our complete revenue tech stack (Salesforce, Marketo, Paid Media, GA4, Gong, ZoomInfo, Lusha, LinkedIn Sales Navigator, BigQuery, and more) as we strive to move towards a Revenue Orchestration Platform, with a mandate to support, integrate, and automate processes across all revenue systems where required.
The team
As a pillar of WGSN’s Revenue Systems function, the Digital Marketing team is a team of SMEs that drives measurable growth across the entire customer lifecycle from brand awareness to sales and retention. We operate at the intersection of strategy and technology across core areas of Performance Marketing, Marketing Automation, MarTech & Operations, and Website Delivery, aligning digital execution with commercial goals while leveraging automation to reduce manual effort and maximise ROI.
Key accountabilities
MarTech Architecture & Automation
Marketo Engineering & Attribution: Architect, optimise, and maintain complex Marketo programs, dynamic templates (utilising Velocity scripting), custom objects, and multi-touch attribution models in collaboration with Marketing Operations, Business Intelligence, and GTM teams.
Lead Lifecycle & Routing: Build and refine end-to-end lead scoring, lifecycle stage transitions, and routing logic between Marketo and Salesforce to ensure efficient & automated sales handoffs.
Data Pipelines & Tracking Infrastructure
Inbound & Paid Media Pipelines: Build and manage SQL-based data pipelines (BigQuery/Snowflake/dbt) and automated extracts connecting our MarTech - GA4, SEO/GEO data, and paid media platforms (LinkedIn, Google Ads, Meta) to the central data warehouse.
System Integration & Webhooks: Design, implement, and monitor robust API integrations, webhooks, and middleware to sync real-time data across Marketo, Salesforce, Revenue Systems tools (Gong, Lusha, ZoomInfo), and data warehouses.
Applied AI & Automation Engineering
Automated Enrichment & personalisation: Develop custom Python/Node.js scripts connecting lead capture channels to LLM APIs (Claude, Gemini) to auto-categorise, enrich, and score inbound/outbound leads in real time.
Unstructured Data & AI Insights: Extract actionable intent signals, sentiment, and competitor mentions from conversational tools (e.g., Gong API) and feed enriched data back into revenue systems and the warehouse.
Emerging Tech Exploration: Experiment with and pilot multi-agent orchestration systems, LLM-powered workflows, and protocols (such as MCP or multi-agent orchestration systems) to automate complex operational and administrative tasks.
Systems Engineering & Custom Development
Custom Scripting & Automation: Write clean, maintainable Python and JavaScript code to automate manual operational workflows and bridge legacy gaps across the revenue ecosystem.
Full Stack Support & Maintenance: Serve as a flexible engineering resource capable of troubleshooting API failures, debugging automation flows, and supporting any platform across the global revenue ecosystem.
This list is not exhaustive, and there may be other activities you are required to deliver.
Skills, experience & qualifications required
Experience & Mindset: 3+ years in MarTech, RevOps, or GTM Engineering, with a proactive builder mindset focused on writing code and building automated pipelines to solve operational inefficiencies.
Marketo Architecture: Expert-level Marketo knowledge (programs, lead lifecycles, webhooks, Velocity scripting, tokens); Adobe Marketo Engage Certified Expert (MCE) or above is highly desirable.
Programming & Scripting: Strong coding skills in Python, JavaScript, SQL, HTML/CSS, JSON, REST/SOAP APIs, and webhooks for system integrations and custom development.
Data Engineering & Analytics: Hands-on experience with BigQuery, Snowflake, or dbt to extract and transform data across Marketo, GA4, GTM, and paid media platforms (Google, LinkedIn, Meta).
Applied AI Integration: Proven ability to interface with LLM APIs (OpenAI, Claude, Gemini) using Python/JS for real-time lead enrichment, intent scoring, dynamic personalization, and workflow automation.
Revenue Tech Stack: Familiarity with Salesforce (Flows/Apex/APIs), revenue tools (Gong, ZoomInfo, Lusha, LinkedIn Sales Navigator), and middleware platforms (Zapier, Make, Workato, Funnel).
DevOps & Developer Tools: Proficient with Git workflows (GitHub/BitBucket), modern AI coding assistants (Claude Code), and project management tools (JIRA).
Stakeholder Management: Demonstrated ability to partner closely with Digital Marketing, the broader Revenue Systems team, Data Engineering, Go-To-Market teams, and executive leaders to translate commercial objectives into technical architectures. Skilled in communicating solutions effectively to stakeholders ranging from Marketing Executives to VP-level leadership.