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 2500 employees working across Europe and the US. We currently serve 60 million consumers, work together with 130,000 merchants and process more than a million payment transactions a day. We're growing at 40% every year and our investors include Visa, Atomico, Sequoia Capital, Permira and Bestseller group/ Anders Holch Povlsen. We have strong partnerships with some of the world’s leading brands, such as ASOS, IKEA, Adidas, Zara, Lufthansa and Spotify.
What you will do
We offer the rare opportunity to curate the whole data journey in a big fintech company. You will work in the Data Domain and enable Klarna to understand, predict and make the right decisions based on large, fast, structured, unstructured and growing amounts of data.The data journey starts in the data producing systems, then travels through the Data Lake, is refined in the Data Warehouse and presented to both internal and external users in the BI Applications. You love solving complex problems, challenging the batch models written, optimizing data models and writing SQL queries. You encourage a social environment at work and share energy and inspiration to your teammates.
Your stakeholders will be Data Scientists, Business Analysts, other Engineers 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 AWS Glue (Spark), AWS Redshift, Apache Airflow, and Qlik Sense. We try to be SQL and code focused; and we are always looking for the most efficient tool for the job.