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Marketing Operations Engineer; MarTech​/GTM Systems

Job in San Jose, Santa Clara County, California, 95199, USA
Listing for: Kadence
Full Time position
Listed on 2026-06-29
Job specializations:
  • IT/Tech
    Digital Marketing, Data Engineering, Data Analyst
Salary/Wage Range or Industry Benchmark: 95000 - 130000 USD Yearly USD 95000.00 130000.00 YEAR
Job Description & How to Apply Below
Position: Marketing Operations Engineer (MarTech / GTM Systems)

Kadence is on a hypergrowth path, building the category-defining workplace operations platform of the future. We’re hiring a Marketing Operations Engineer to be the architect and technical backbone of Marketing, optimizing the tools, data, and automation that power Demand Gen, ABM, and bowtie GTM execution. You’ll manage a complex Mar Tech stack, ensure seamless data flow, and leverage data + automation (including AI) to drive efficiency and measurable revenue growth across acquisition and expansion.

Core

platforms:

Hub Spot, Intercom, Word Press, Demio (plus connected GTM tools like Zoom Info, Clay, etc.)

What you’ll do
  • Own and optimize the marketing tech stack (Hub Spot & connected tools), ensuring scalability, governance, documentation, and high reliability.
  • Architect seamless data flow across Hub Spot, Intercom, Word Press, Demio, Paid Media (Google Ads/Linked In), and other systems to enable clean integrations, consistent fields/taxonomy, and trustworthy lifecycle tracking.
  • Operationalize Demand Gen and ABM execution: segmentation, lead scoring, routing, nurture programs, campaign QA, and attribution that Sales and Marketing can depend on.
  • Support a bowtie sales model by enabling both new logo and expansion motions with lifecycle triggers, handoff workflows, and automated follow-up systems that reduce friction and speed up revenue.
  • Build and maintain reporting that connects activity to pipeline funnel dashboards, campaign health, and clear conversion/velocity insights.
  • Drive automation and efficiency (including AI): identify bottlenecks and replace manual work with workflows, enrichment, QA checks, experimentation support, and AI-assisted operational systems.
  • Bridge marketing strategy and technical execution by partnering closely with Demand Gen, Content, Product Marketing, Rev Ops/Sales Ops, CX, and Leadership, in addition to collaborating with Engineering when needed on tech troubleshooting and integrations.
Qualifications
  • 4–8+ years in Marketing Ops / Rev Ops / Marketing Systems / Growth Ops, ideally in B2B SaaS.
  • Deep hands-on experience with Hub Spot is critical to this role (workflows, lifecycle stages, lists/properties, automation, reporting, governance).
  • Strong understanding of Demand Gen & ABM mechanics and how to operationalize them through systems, processes, and measurement.
  • Proven ability to manage data quality and lifecycle integrity (de‑dupe, enrichment, routing rules, field standards, attribution, compliance basics).
  • Technical proficiency connecting systems (APIs/webhooks/iPaaS tools), troubleshooting integrations, and building durable, scalable processes.
  • Experience with data/enrichment and prospecting ops tools such as Zoom Info and Clay (enrichment workflows, account/lead sourcing, segmentation support, and data hygiene).
  • Demonstrated utilization of AI tools for marketing operations such as workflow automation, enrichment/qualification support, campaign QA, performance insights, routing logic, and internal tooling, applied safely and systematically.
  • Strong analytical skills: can design reporting that the business trusts and use insights to improve conversion, velocity, and pipeline impact.
  • High ownership, fast execution, and comfortable operating in ambiguity in a fast-moving Series‑A environment.
Preferred
  • Familiarity with Word Press marketing ops (tracking, forms, conversion paths, SEO/landing page workflows).
  • Experience supporting Linked In campaign workflows and matching ad data to CRM/lifecycle outcomes.
  • Experience running webinar/event funnels using webinar platforms (ex. Demio/Livestorm)
  • Experience building repeatable AI-assisted ops playbooks (prompt/agent standards, QA guardrails, data handling practices, and measurable time/pipeline impact).
  • Experience with chatbot platform (ex. Intercom/Drift) playbook workflows and integrations.
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