Demand Generation Systems Operator
Demand generation and GTM leader with 15+ years of professional marketing experience. At CData, as Director of Demand Generation, I led three Senior Managers and their teams and made channel and vendor investment decisions. Across roles, I have aligned Marketing and Sales around demand, SQL, and pipeline outcomes.
Open to full-time Senior Manager, Director, and Director-track roles across demand generation, growth, PLG, and GTM systems. Remote preferred; selective Seattle-area hybrid.
Leadership and scale
15+ years
Professional marketing experience
3 senior managers
Direct reports, each leading a team, as Director of Demand Generation at CData
~$25K–$50K / month
CData channel and vendor allocation authority, not company-wide budget ownership
+60%
Lead generation at KnowledgeLake from a redesigned campaign strategy
15+ AWS teams
Supported through Grazitti as senior demand and account lead, without reporting authority
+30% SQL / +15% pipeline
At CData within six months; not attributed to one decision or to team management
Experience spans cybersecurity, SaaS, cloud infrastructure, enterprise technology, PLG, ABM, lifecycle, paid acquisition, marketing operations, analytics, and decision-ready reporting. Metrics above span more than one role and are presented as career-scale evidence, not one combined program.
When a PPC vendor's reported performance lacked persuasive downstream business evidence, I chose not to renew the contract. I redirected investment toward a quarter-long niche-community experiment with subject-matter expert participation. The decision was about where the next dollar should go, not which channel looked busiest.
The replacement test has no claimed measured ROI. CData's broader SQL and pipeline growth is reported separately and is not attributed to this vendor decision.
The systems I operate
01
Make complex cross-functional execution runnable.
I turn fragmented campaign work into a system with explicit ownership, dependencies, decision points, measurement requirements, and operating cadence.
02
Separate acquisition activity from actual customer progress.
I connect acquisition, activation, qualification, lifecycle, sales handoff, and revenue evidence so teams know what is working, what is merely moving, and what remains unproven.
03
Turn reporting into a recommendation.
I structure performance evidence around what changed, why it matters, what remains uncertain, and what the business should do next.
Visibility → Optimization → Decision → Alignment
Selected proof of work
Campaigns were launching, but ownership, sequencing, and stakeholder visibility were inconsistent. Cross-functional teams were spending too much time renegotiating how work moved instead of executing the work itself.
A free-trial motion needed a way to tell whether a trial conversion represented real progress: whether it could be connected through provisioning, activation, product usage, qualification, sales follow-up, and revenue.
Campaign data existed. Decisions did not. Reporting was descriptive but not actionable, which left interpretation work to the audience.
Trial pages were being built one-off per campaign, which slowed iteration, drove inconsistent messaging, and made conversion learning difficult to compare across waves.
Campaign documentation, QA, and readouts were consuming time disproportionate to the value produced. Quality drifted whenever execution pressure rose.
Selected career impact
Outcomes are role-specific and are not presented as one combined attribution claim.
Applied decision tools
These are portfolio-built demonstrations of decision logic and tradeoffs. They are not presented as evidence of real-world business outcomes.
Trace how product usage, buying-group evidence, customer context, and governance become coordinated revenue action.
Open toolAssess whether a free-trial motion is ready across offer, activation, lifecycle, routing, and reporting.
Open toolInject a constraint into a demand system and trace what breaks downstream, what stays healthy, and where to intervene.
Open toolOperating system
Start from the business outcome, not the channel calendar.
Most campaign work fails because the goal is restated as an output. The first step is converting an executive goal into the campaign-level decisions that have to be made and the cross-functional pieces that have to be in place before launch.
Make the seams visible before optimizing the parts.
A campaign is an audience, message, offer, page, handoff, data flow, sales motion, reporting layer, and feedback loop. Mapping how work actually moves between those parts surfaces the bottleneck faster than any individual channel review.
Decide once, not per campaign.
RACI matters most when it covers recurring campaign types instead of one-off launches. The goal is fewer ownership debates inside the work and faster scoping at the front of it.
Structure first, traffic second.
Paid spend on a broken structure is expensive learning. The launch sequence prioritizes the structural fixes that make the campaign measurable, then layers traffic on top.
Reporting that ends in a recommendation is harder to write and easier to act on.
Descriptive reporting tells leadership what happened. Decision-ready reporting tells them what to do. The interpretive layer is where most reporting effort should go.
Contact
Open to full-time Senior Manager, Director, and Director-track roles in demand generation, growth, PLG, and GTM systems. Remote preferred; selective Seattle-area hybrid.