Marketing Operations Engineer

About SecurityScorecard:

SecurityScorecard is the global leader in cybersecurity ratings, with over 12 million companies continuously rated, operating in 64 countries. Founded in 2013 by security and risk experts Dr. Alex Yampolskiy and Sam Kassoumeh and funded by world-class investors, SecurityScorecard’s patented rating technology is used by over 25,000 organizations for self-monitoring, third-party risk management, board reporting, and cyber insurance underwriting; making all organizations more resilient by allowing them to easily find and fix cybersecurity risks across their digital footprint.

Headquartered in New York City, our culture has been recognized by Inc Magazine as a "Best Workplace,” by Crain’s NY as a "Best Places to Work in NYC," and as one of the 10 hottest SaaS startups in New York for two years in a row. Most recently, SecurityScorecard was named to Fast Company’s annual list of the World’s Most Innovative Companies for 2023 and to the Achievers 50 Most Engaged Workplaces in 2023 award recognizing “forward-thinking employers for their unwavering commitment to employee engagement.” SecurityScorecard is proud to be funded by world-class investors including Silver Lake Waterman, Moody’s, Sequoia Capital, GV and Riverwood Capital.

About the Role:

We are looking for a Marketing Operations Engineer to help us build the next generation of GTM systems, marketing automations, and AI-powered workflows optimizing the full journey of marketing leads to pipeline conversion.

Reporting to the Director, Marketing Operations & Analytics, you will work across Salesforce, Marketo, Clay, Artisan, Qualified, ClickUp, Claude Code, and the broader GTM stack to turn business problems into practical, scalable solutions.

This is a hands-on builder role. You will partner with teams across Marketing, Business Development, Revenue Operations, Sales, Finance and IT to drive greater operational rigor within marketing and drive solutions yielding quality pipeline at scale.

The right person will have a strong MarTech foundation, an acumen for aligning technical solutions to business outcomes and a genuine interest in how AI is changing the way GTM teams operate.

This role follows a hybrid work model based on proximity to our office locations. Employees who live within 75 miles of our Midtown NYC or Downtown Austin office are required to work onsite 1–2 days per week. Employees who live outside a 75-mile radius of both offices are eligible for fully remote work.

Key Responsibilities

Build and improve AI-powered workflows and agents using Claude, Claude CoWork, Clay and Artisan to power demand generation and BDR motions.

Implement enrichment and signal-detection tooling, like Clay, to uplevel data governance.

Use Claude Code and other AI development tools to prototype, build, test, and troubleshoot solutions.

Deploy AI automation into the marketing project management and intake request model, ensuring alignment with SLA framework for on-time delivery of quality campaigns.

Improve marketing effectiveness by building a rigorous approach to operational processes impacting pipeline generation target attainment.

Support ongoing user enablement and adoption of the GTM stack.

Design and manage signal-based triggers, including lead scoring and routing in partnership with BDR and Sales teams.

Develop and manage data models and scoring layers for customer propensity, ICP attribution, and lead and account scoring.

Scale and optimize repeatable, data-driven plays across marketing channels to improve lead-to-meeting conversion, pipeline generation, and funnel efficiency.

Develop marketing lead lifecycle and qualification processes to ensure prospects and customers receive timely, relevant follow-up from our sales teams.

Administer marketing database strategy including growth, enrichment, hygiene, and governance.

Develop applications surfacing insights to improve top, middle and bottom-of-funnel inbound processes and activity.

Document and communicate what you build so solutions can be maintained and improved over time.

Measure whether the solutions you build are improving adoption, efficiency, data quality, or business outcomes.