If you’re in Sales or Revenue leadership, you’ve probably noticed a shift happening. Advances in data, automation, and AI have unlocked huge opportunities, but they’ve also added complexity. RevOps remains a vital function, but the sheer volume of tools, integrations, and signals means it now needs a technical partner. That’s where GTM Engineering comes in.
Think of GTM Engineering as the technical backbone of modern revenue teams. It’s a hybrid role that blends data engineering, operations, and automation with one mission: helping GTM teams sell smarter, faster, and more efficiently.
In this guide, we’ll break down what GTM Engineering really is, why it matters, and how to build your first GTM Engineering function.
What is GTM Engineering?
Why GTM Engineering matters
The GTM Engineer role explained
KPIs and success metrics
Org design models
How to build a GTM Engineering function
Next steps
GTM Engineering is the practice of designing and maintaining the systems, data flows, and automations that power sales, marketing, and customer success teams. Where RevOps sets the strategy, GTM Engineers execute on the technical side, building pipelines, integrating tools, and making sure everything works together.
It’s a function born out of necessity. As tech stacks have ballooned and data complexity has increased, traditional RevOps teams often lack the bandwidth or technical depth to keep things running smoothly. GTM Engineering fills that gap.
Let’s face it: most revenue teams are drowning in tools. CRMs, data warehouses, marketing automation, enrichment APIs, dashboards… the list goes on. Without someone responsible for stitching it all together, you end up with:
• Broken lead routing
• Reps wasting time on admin
• Misaligned data between sales and marketing
• Poor visibility into the pipeline
A GTM Engineer fixes these problems at the root. They create order from chaos, enabling your go-to-market teams to focus on selling.
So what exactly does a GTM Engineer do day-to-day? Here are the core responsibilities:
• Data pipelines: Syncing data between your CRM, marketing automation, and data warehouse.
• Automation: Building lead routing, scoring, and enrichment workflows.
• Integration: Connecting tools like Salesforce, HubSpot, Jiminny and Slack.
• Experimentation: Partnering with GTM teams to test new processes or tools.
• Governance: Ensuring data quality and compliance.
In short: if RevOps says, “We need faster lead follow-up,” the GTM Engineer makes it happen from a technical standpoint.
You can’t manage what you don’t measure. Common KPIs for GTM Engineering include:
• Hours saved for reps and managers
• Lead routing accuracy
• Time-to-lead-response
• System uptime and sync reliability
• Meetings booked per GTM Engineer headcount
The impact should be tangible: faster processes, less friction, and more closed revenue.
Where should GTM Engineers sit in your org? There are three common models:
• Embedded: Each GTM team (Sales Ops, Marketing Ops, CS Ops) gets an embedded GTM Engineer.
• Centralized Pod: A GTM Engineering team serves the whole org, taking requests and prioritizing projects.
• Hybrid: A small central team with engineers embedded on critical projects.
For startups, embedding often works best. As you scale, a centralized pod provides leverage and governance.
If you’re thinking of building a GTM Engineering function, start small. Here’s a suggested rollout to implement in-house (if you have the capacity within your RevOps team) or by hiring a GTM Engineer:
Days 1–30: Discovery & Audit
1. Map your current GTM tech stack (CRM, marketing automation, CS tools, data warehouse, enrichment APIs).
2. Interview Sales, Marketing, and CS leaders to uncover pain points and bottlenecks.
3. Audit lead routing, scoring, and enrichment workflows and identify where they break.
4. Document data flow diagrams (where does data come from, where does it live, where does it go).
Days 31–60: Quick Wins
1. Prioritize the “low-hanging fruit”: the fixes that save reps the most time. For example automating lead routing from inbound forms to reps, standardizing enrichment fields so reps stop wasting time cleaning data or building Slack alerts for hot leads or stalled deals.
2. Set up monitoring on data syncs (so you know when Salesforce/HubSpot is breaking before reps complain).
3. Begin training RevOps leaders on what GTM Engineering can (and cannot) do.
Days 61–90: Scalable Foundations
1. Stand up a warehouse-native GTM architecture (Snowflake, BigQuery, Redshift) and integrate it with your CRM.
2. Build reusable data pipelines (reverse ETL via Census/Hightouch; enrichment with Clearbit/ZoomInfo).
3.Implement governance rules: naming conventions, data quality checks, change-management process.
4. Establish KPIs: hours saved per rep, lead response time, system uptime, revenue influenced.
By the end of 90 days, your GTM Engineer should have delivered visible improvements (reps saving time, fewer broken processes) and laid the groundwork for scaling. This gives leadership confidence and builds internal momentum for investing further.
GTM Engineering isn’t a nice-to-have anymore it’s becoming a core function of high-performing revenue teams. By investing in it early, you’ll free up your reps to focus on selling, give leadership cleaner data, and gain a competitive edge.
At Jiminny, we’ve seen firsthand how powerful the right GTM infrastructure can be. With conversation intelligence, deal insights, and AI-powered coaching, we help GTM teams not just capture data, but put it to work.
Ready to explore how GTM Engineering and Jiminny can supercharge your go-to-market strategy? Book a free demo today.