Who we are Klarna’s mission is to free people from all the meaningless time spent managing money and purchases, so they can do more of what they love.
Every day at Klarna we help consumers, merchants, and partners to explore just how smoooth the modern purchase experience can be.
Our position at the crossroads of payments, consumer financing, ecommerce and banking means we are uniquely positioned to do this.
There is no label for what we do. Klarna was born in Stockholm in 2005 and today has 2000 employees working across Europe and the US.
We currently serve 60 million consumers, work together with 90,000 merchants and process more than a million payment transactions a day.
We are growing at 40% year on year and our investors include Visa, Atomico, Sequoia Capital, Permira and Bestseller group / Anders Holsch Povlsen.
We have strong partnerships with some of the world’s leading brands, such as ASOS, IKEA, Adidas, Zara, Lufthansa and Spotify.
To find out more about what it's like to work at Klarna : klarna.com / careers What you will do As a business intelligence developer you will work in a team of data engineers with end to end responsible for data products, where a data product spans from management dashboards, data warehousing, frameworks for development and quality measures.
You will mainly design and develop Qlik Sense and other reporting / dashboarding solutions, but you could also work with the datalayers optimising a data pipeline or model.
You enjoy solving complex problems and displaying the results in spectacular dashboards, interactive reports and challenge the current models of consuming information.
You encourage a social environment at work and share energy and inspiration to your team-mates. Your stakeholders will be Data Scientists, Business Analysts and all Klarna employees that need data in their daily work.
We have amazing teams that take care of and become experts at different parts of the domain where sharing and collaboration are key.
Some of the technologies and languages we use are Qlik Sense, AWS Redshift, Apache Airflow - and we are always looking for the most efficient tools for the job.
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