[Hiring] Enterprise Account Executive @Polar Analytics

Role Description

We're closing enterprise deals already. Q1 2026 was a company record. The unit economics are strong: $40k ACV, <30 days close time on qualified deals, 40% win rate.

But enterprise deals are getting more complex. They require:

• Executive stakeholder mapping
• Build vs buy positioning against internal data teams
• Longer cycles with multiple decision-makers

We need someone who can run these deals end-to-end - from first call to close - with the technical credibility and deal orchestration skills that enterprise requires.

You'll work alongside our Head of Sales and partner closely with our partnerships team. The opportunity is massive and the foundation is built - we need someone who can close at the next level.

What you'll own

• Full-cycle enterprise deals from discovery through close targeting mid-market and enterprise DTC brands doing $50M-$500M+ GMV with complex omnichannel operations.
• Executive stakeholder mapping and multi-threaded selling across ecommerce, marketing, data, and finance teams.
• Build vs buy conversations with technical stakeholders.
• Pipeline generation in partnership with our SDR function, partnerships team, and your own outbound.
• AI and MCP demos that land.
• Consultative discovery using our structured playbook.
• Deal forecasting and pipeline hygiene.

Qualifications

• 3-5 years closing $50k+ enterprise SaaS deals with technical evaluation processes.
• Experience selling to multi-stakeholder buying committees.
• Technically credible with the ability to discuss semantic layers, Snowflake instances, attribution models, and data architecture.
• Experience selling to ecommerce, retail, or DTC brands, or data/analytics/BI tools.
• Consultative seller who positions as a strategic advisor.
• Patient with long cycles but relentless on next steps.
• Comfortable demoing AI products live.
• Clear and concise communicator.

What separates A-players

• Run discovery like a consultant, mapping every stakeholder in the first two calls.
• Pivot between talking ROAS with a Head of Growth and data architecture with a CTO in the same meeting.
• Build pipeline when ahead of quota, not just when behind.
• Treat forecasting as a craft; commits are accurate based on understanding deals.

What our customers see

• Thiege consolidated 9 different tools into Polar and saved $300K per year vs building their own data stack.
• CABA improved their ROAS by 65% using our attribution model and incrementality testing to reallocate spend.
• Modular Closet grew Klaviyo flow revenue by 50% with our CDP and identity resolution layer.
• Quadlock started with us below $10M - we helped them scale to 9 figures and a $350M acquisition.