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๐ŸŽ‡Senior Analytics Engineer

Polar Analytics

Polar Analytics

Data Science
Posted on Friday, June 2, 2023

Senior Analytics Engineer

Job Edited on
October 3, 2022 9:17 AM
Remote (Europe Timezone)

Polar Analytics: What, Why, How & Where

What weโ€™re looking for

We're looking for individuals who love to create products and have ownership from inception to shipping.
We live in a moment where growing with data has never been more essential: your mission at Polar will be critical. Weโ€™re looking for people who love to grow and empower brands to grow with data.
Finally, we're looking for humble innovators, people who have crazy ideas and who value impact more than anything else.

Why this role?

Unlike other Analytics Engineering roles, you will work on the core product. You will help empower thousands of entrepreneurs to grow their brand, with a product they use daily
Have an impact on the future of the modern data stack for eCommerce, working on core technologies like dbt, snowflake, airbyte, airflow, airtbyte, fivetran
Have strong ownership as #1 Analytics Engineer on the team, and grow a product that is already used by 900+ brands
Join us at one of the most exciting moments of our history: we are building the core features of the app with $9M raised and a growth rate of 30% month-over-month

Whatโ€™s the scope

You will own data modelling at Polar:
Create models from scratch that will empower brands to answer new data questions
Write tests to ensure that your models produce the right results and detect edge cases
Maintain existing models and schema evolutions
Create a data catalog as tables will be directly used by the end user
You will own metrics & dimensions definitions on the app. We have created an eCommerce metrics layer (the synthesizerโ„ข), which is a centralised, single source API that can compose metrics and dimensions flexibly
Create new metrics & dimensions
Document new and existing metrics & dimensions
Optimise end queries to ensure great performance
You will help design data modelling & warehouse architecture alongside data engineers to scale our data modelling
Automate and setup best practices in the analytics workflow (tests, dbt, github)
Write macros to deal with incrementality and multi-tenancy
You will work closely with Product to gather and translate requirements into technical solutions to achieve the maximum impact

The job is made for you if...

๐Ÿค– You love building data models from scratch and reasoning about data architecture
๐Ÿ’ƒ You are passionate about data products: you want to have an impact on the future of the modern data stack
๐Ÿš€ You have already worked in a production environment with multiple users
๐Ÿ• You have spent a meaningful time (5+ years) as a hands-on data analyst / analytics engineer
๐Ÿฆพ You are fluent with SQL and have good knowledge of Python
๐Ÿ‘€ You are curious, with an active technological watch
๐ŸŽ– You have a sense of ownership and responsibility

Being an Engineer at Polar Analytics

Getting Stuff Done, Ownership, Excellence, and Agility.
At Polar, engineers have a lot of ownership, as they both build features and make crucial product decisions.
You should join us if you want to ship fast without sacrificing quality, and be a part of a growing team that thrives for excellence.

Our stack

We like to try new things out but most of our data stack is built around SQL & Python. Here are the things we use - and love:
Airbyte & Fivetran
Micro-services architecture on AWS

Company Perks & Benefits

๐ŸŒŽ Remote-first organisation with a culture around impact rather than hours
๐Ÿ– 5 weeks of vacation
๐Ÿ’ฐ Competitive salary & equity (90th percentile of the market worldwide)
๐Ÿ’ป Latest MacBook Pro or equivalent
๐Ÿฉบ Complimentary private health insurance (we use Alan)
๐Ÿ˜ Every quarter we organize a company-wide offsite to discuss where we're going and strengthen the social bonds

Hiring process

We like to move fast but want to give you a chance to meet as many team members as possible:
Introduction chat with Head of Talent: vision, progress, milestones, past experience, what you like working on, etc. remote - 30 mins
Technical fit (Ways of working, business / product discussion) with CTO - 45 mins
Technical test (Coding & Knowledge questions) with Lead Data Engineer. Similar to problems weโ€™ve worked on. Live test - 1 hour
Culture Fit with CEO - 45 mins
2 final steps:
2-way ref check. You chat with our investors, customers, & partners. We chat with previous (or current) coworkers/managers.
Offer. 3 options. 1 high equity. 1 high base. 1 mid equity/base. You also get to see our cap table, revenue, burn, customer pipeline, & state of the company

How to Apply