Enterprise Account Executive

Polar Analytics; Palo Alto (CA); Hybrid; USD 100,000 - 150,000; Full time

Job summary

A leading analytics provider is seeking an experienced enterprise sales professional to lead complex deals from discovery to close. You will engage with multi-stakeholder buying committees in ecommerce and DTC brands, showcasing AI product capabilities and navigating difficult technical conversations. The ideal candidate has at least 3-5 years of experience in closing $50k+ SaaS deals and excels at consultative selling. This role requires strong communication and relationship-building skills to manage long sales cycles effectively.

Qualifications

• 3-5 years of experience closing $50k+ enterprise SaaS deals.
• Ability to discuss technical topics confidently without a script.
• Experience in ecommerce, retail or selling data/analytics/BI tools.

Responsibilities

• Own full-cycle enterprise deals from discovery to close.
• Map executive stakeholders and manage multi-threaded selling.
• Conduct demos of AI products confidently and explain the AI roadmap.
• Ensure accurate deal forecasting and maintain pipeline hygiene.

Skills

Enterprise sales experience

Technical credibility

Consultative selling

Relationship building

Clear communication

Live demoing of AI products

Job description

Why this role exists

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, and 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.

What you'll own

• Full-cycle enterprise deals from discovery through close. Your targets will be 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. You'll navigate deals where the CRO, VP of Ecommerce, and CFO all need to sign off.
• Build vs buy conversations with technical stakeholders. Brands with data teams are evaluating building their own stack – you need to credibly position why 8 separate tools and a 6-12 month project isn't the answer. Your talk track branches based on team size and sophistication.
• Pipeline generation in partnership with our SDR function, partnerships team, and your own outbound. You'll own the number and know it cold – the trend, the why, the plan.
• AI and MCP demos that land. Our AI roadmap – semantic layer, AI data analyst, AI strategist, autonomous agents – is the strongest part of our pitch for enterprise. You need to demo MCP on Claude and ChatGPT live and explain the four-level AI journey confidently.
• Consultative discovery using our structured playbook. We've built discovery frameworks for goals, stack, pain/product, and decision process – you'll master them and make them your own.
• Deal forecasting and pipeline hygiene. No silent slips – if something is off, say it now. Reforecast early with a new plan, don't wait for it to blow up.

Who you are

• You've spent 3-5 years closing $50k+ enterprise SaaS deals with technical evaluation processes. You've sold to multi-stakeholder buying committees, not just single-threaded to one champion.
• You're technically credible. You can discuss semantic layers, Snowflake instances, attribution models, and data architecture without sounding like you're reading a script. CTOs and data leads take you seriously.
• You have experience selling to ecommerce, retail, or DTC brands – or you've sold data/analytics/BI tools and can learn the vertical fast.
• You're a consultative seller who positions as a strategic advisor, not a vendor. You help prospects understand their data architecture gaps and business impact before you pitch features.
• You're patient with long cycles but relentless on next steps. Enterprise deals require relationship building across multiple stakeholders – you know how to keep momentum without being pushy.
• You're comfortable demoing AI products live and excited about the space. This isn't a "hand it to the SE" role – you run your own demos.
• You communicate clearly and concisely. No fluff, no jargon. You close the loop on everything.

What separates A-players

You run discovery like a consultant, not a checklist. You map every stakeholder in the first two calls and know exactly who the economic buyer is. You can pivot between talking ROAS with a Head of Growth and data architecture with a CTO in the same meeting. You build pipeline when you're ahead of quota, not just when you're behind. And you treat forecasting as a craft – your commits are accurate because you understand your deals, not because you're sandbagging.

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.