Enterprise Account Executive

polaranalytics; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Polar is seeking a seasoned Enterprise SaaS closer to drive full-cycle, multi-department deals with ecommerce and DTC brands. You will map executive stakeholders, conduct build vs. buy conversations, and manage long sales cycles while presenting live AI demos and articulating the company’s AI roadmap.

You will own pipeline generation with cross-functional teams, target mid-market to enterprise accounts, and maintain sharp forecasting to meet ambitious close rates.

Qualifications

• 3–5 years closing $50k+ enterprise SaaS deals with technical evaluation processes.
• Experience selling to ecommerce, retail, or DTC brands.
• Ability to map stakeholders and manage long sales cycles across multiple departments.
• Comfort with live AI product demos and technical storytelling.

Responsibilities

• Own full-cycle enterprise deals from discovery through close for mid-market and enterprise DTC brands with complex omnichannel operations.
• Execute executive stakeholder mapping and multi-threaded selling across ecommerce, data, marketing, and finance teams.
• Lead build vs buy conversations with technical stakeholders and articulate data-architecture considerations.
• Partner with SDR and partnerships teams to generate pipeline and own the number.
• Demonstrate MCP/AI demos live and explain the AI roadmap to enterprise buyers.
• Maintain accurate pipeline forecasts and proactively reforecast with a updated plan.

Skills

Enterprise SaaS

Multi-stakeholder sales

Technical credibility

Consultative selling

AI product demos

Forecasting & pipeline

Executive stakeholder mapping

Tools

Snowflake

Claude/ChatGPT

CRM

Job description

Who we are

Polar is the complete data platform for omnichannel commerce. We connect every data source a brand runs on - Shopify, Amazon, NetSuite, Meta, Google, Klaviyo - into a single Snowflake warehouse, layer a commerce semantic layer on top, then add AI so operators can ask questions, get answers, and automate workflows without writing SQL.

Our founders came from Turo and Airbnb in Silicon Valley. They built data platforms at scale and wanted to bring that level of sophistication to fast-growing commerce brands. We support 4,000+ merchants, and zero direct competition with a better solution. We serve brands like Quadlock, gorjana, Joseph Joseph, and ARMRA Colostrum.

We shipped MCP integrations with Claude and ChatGPT, AI automations, and an AI Data Engineer that builds connectors on demand. Our positioning: the data layer to build agent workflows for commerce. Customers tell us things like "this is a dream come true - it feels like the first time they showed me Shopify".

How we operate

We publish our operating principles internally and we mean every word. Here are the ones that matter most if you're thinking about joining:

Customer Obsession. Every decision starts with: does this make our users' lives better? If the answer isn't clear, go talk to a customer before you build anything.

Own the Number. Every metric has an owner. If it's yours, know it cold - the trend, the why, the plan. Don't wait for someone to ask. If it's off track, you should be the first to say so.

Raise the Pace. Always ask: what would it take to do this in half the time? Speed is our edge. We try 100 things while the competitor tries one.

Don't Fail Silently. If it's broken, say it. If you're stuck, raise your hand. Hiding problems is the one thing that will actually get you in trouble.

Here to Win, Not to Be Right. Quiet ego, loud standards. Don't fight to be right - fight to win together. Be ruthless on quality, never rude about it.

Optimize for Polar, Not Your Function. "Not my scope" doesn't exist here. If it makes us win, it's your scope.

We're a remote-first team that runs daily standups, ships weekly, and holds ourselves to a standard most companies talk about but don't enforce. We're transitioning from founder-led intensity to systematic company intensity - which means we need people who can maintain the pace autonomously, not just when someone's watching.

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.

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. 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 blow up
  

Who you are

We don't have a rigid checklist of requirements. We're looking for a specific kind of person:

• 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

These are the kinds of results you'll sell against:

• 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

How we hire

We believe the best people want to go through a demanding process. We've learned the hard way that great interviewers aren't always great operators - so our process is designed to see how you think, not how you present.

1. Motivation screen - A quick call to understand what drives you and whether there's mutual fit

2. Live case study - A real scenario where you work through a problem in real time. No prep decks, no take-homes. We want to see how you actually operate

3. Leadership conversations - Meet the team, understand the culture, make sure this is somewhere you want to build

Our hiring bar: if this person started a company, would we want to join them?