Senior Marketing Analyst, Data & Analytics

Role Overview

We are looking for a strategic Senior Marketing Analyst to join our growing data and analytics (DNA) team at Thomasnet.com. This role sits at the intersection of marketing performance, data engineering, and executive storytelling. You will own paid marketing analytics end-to-end: building the data infrastructure that powers our reporting, running attribution analysis across channels, and translating complex data into the clear narratives that drive budget, strategy, and product decisions.

What You Will Do

You will own paid marketing analytics end-to-end: building the data infrastructure that powers our reporting, running attribution analysis across channels, and translating complex data into the clear narratives that drive budget, strategy, and product decisions.

Why It Might Be a Fit

This role bridges Marketing, Sales, Yield, and Product. Your work will directly influence how we allocate marketing spend, price our inventory, and grow revenue.

Requirements

• 5+ years in marketing analytics, growth analytics, or a closely related field — ideally in a marketplace, B2B SaaS, AdTech, or lead-gen environment
• Demonstrated experience owning paid marketing analytics (Google Ads, Microsoft Ads, Meta); you understand how the platforms work, not just how to report on them
• Track record of producing analysis that changed a decision — and you can tell that story in an interview
• Expert-level SQL; strong Python for data manipulation and analysis
• Hands-on with Snowflake and dbt (or equivalent modern data stack)
• Proficient in Looker (or Tableau/similar) — you build dashboards that people actually use
• Familiarity with Google Ads API, Microsoft Ads API, Segment event tracking, and CRM data (Salesforce, HubSpot)
• Bonus: experience with ad servers or yield platforms (Kevel, Placements.io)
• Exceptional written and verbal communication — you write crisp, jargon-free analyses that a CMO would forward to a CEO
• Ability to structure ambiguous problems, frame a hypothesis, and present findings with confidence and a point of view
• Comfort presenting to senior stakeholders; you don’t hide behind the data, you use it to make an argument
• Deep understanding of paid marketing KPIs: ROAS, CPC, CPL, impression share, quality score, attribution windows
• Familiarity with marketing attribution methodologies (last-click, data-driven, multi-touch)
• Understanding of lead funnels from impression through conversion and renewal

Tagged as: Attribution Modeling, Data Analysis, HubSpot, Looker, Python