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Polar Analytics

Software Engineer (Data & AI)

Reposted 10 Hours Ago
Be an Early Applicant
Remote
Hiring Remotely in EU
20K-70K Annually
Mid level
Remote
Hiring Remotely in EU
20K-70K Annually
Mid level
As a Software Engineer at Polar Analytics, you will build core systems, manage data pipelines, and innovate solutions for eCommerce brands while engaging with users to improve reliability and performance.
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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.

Who we are

We’re building the data & AI operating system for eCommerce, think Datadog for retail.

We ingest messy Shopify, ads, and retention data, make it reliable, and turn it into decisions teams can actually trust.

We’re hiring engineers who want real ownership.

What you will do

You’ll work on core systems: data pipelines, semantic layers, RAG, AI evaluation, experimentation,and products used daily by thousands of merchants.

This isn’t a ticket-taking role. You’ll:

  • Own problems end-to-end (design → production)

  • Tackle hard infra challenges (petabytes, near real-time, high reliability)

  • Talk directly to users to understand failure modes + edge cases

  • Ship fast prototypes, then harden them into real systems

  • Help shape what we build next as we scale

We move quickly, optimize for leverage, and care a lot about doing things right as we grow. We use Claude Code and Cursor very heavily.

If you’re looking for more impact and responsibility than your current role offers, apply below :)

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?

Polar Analytics San Francisco, California, USA Office

San Francisco, CA, United States

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