Job Description

We are seeking a highly analytical, technically proficient GTM Engineer to own the data, AI workflows, systems and operating processes that move demand from targeting and lead creation through qualified early-stage pipeline. This is a hands-on builder role at the intersection of GTM Operations, analytics and GTM Engineering. The successful candidate will establish trusted reporting infrastructure, turn funnel data into decisions, and build governed AI-enabled workflows that materially improve lead quality, conversion, speed and SDR productivity.

What You'll Do (Key Responsibilities)

Analytics, Data and Decision Infrastructure:

• Own the analytical foundation for the lead-to-opportunity funnel, including the data model, metric definitions, source-of-truth logic, transformations and dashboard architecture.
• Build reliable reporting for volume, conversion, velocity, acceptance, aging, leakage, pipeline value and target-account penetration across source, campaign, segment, persona, account tier, channel and owner.
• Evaluate lead-scoring efficacy, routing performance, outreach productivity and handoff quality using cohort, trend and root-cause analysis; translate findings into prioritized actions.
• Create data-quality monitoring, reconciliation and reporting QA so leaders can trust funnel insights and understand metric lineage.
• Develop recurring early-pipeline outlooks and decision-ready performance narratives that clearly identify risks, opportunities and recommended interventions.

What You'll Need (Required Knowledge, Skills & Abilities)

• 4+ years of experience in GTM Operations, Revenue Operations, Sales Operations, Marketing Operations, GTM Engineering, Revenue Systems or an equivalent technical GTM role in a B2B technology or SaaS environment.
• Advanced analytical ability, including experience designing data models, metric definitions, dashboard architecture and scalable reporting infrastructure for operational and executive decision-making.
• Strong Salesforce proficiency across data modelling, process design, automation, reports, dashboards, permissions and data-quality governance.
• Demonstrated success building and operationalising AI-enabled workflows using low-code tools, integrations, APIs or agent-based platforms.
• Working knowledge of AI workflow design, including prompt design, structured outputs, testing and evaluation, monitoring, exception handling and human oversight.
• Hands-on experience administering or optimising a sales engagement platform such as Salesloft or Outreach.
• Experience designing lead lifecycle, scoring, routing, qualification, SDR and early-stage pipeline processes.
• Ability to combine quantitative analysis with commercial judgement, communicate clear recommendations and influence cross-functional leaders.
• Strong requirements-gathering, process-mapping, solution design, testing, documentation and change-management skills.

What Would Be Nice (Preferred Experience)

• Experience with Lusha, Clay, Nooks, Qualified and LinkedIn Sales Navigator.
• Experience with SQL, BI tools, data transformation, reverse ETL or warehouse-based reporting.
• Experience building GTM applications, internal tools or agents in a GTM Engineer capacity.
• Experience supporting enterprise account-based or target-account motions, ideally in identity verification, fraud, cybersecurity or financial services technology.