Analytics Engineer
On our path to becoming the world’s favorite way to shop, we’re assembling an unparalleled global talent network, accelerating individual careers, and disrupting entire industries. We are on a mission to liberate humanity from all the meaningless time spent managing their purchases and finances, so they can do more of what they love. We’re in search of global talent eager to embrace our atmosphere and defy their own expectations.
Engineering at Klarna is an inspired, customer focused community, dedicated to crafting solutions that redefine our industry. Working in small, highly collaborative Agile teams, you and your team will have a clear mission and ownership of an important outcome that supports Klarna and our customers. At Klarna we optimize for quality, flow, fast feedback, focussing on end-to-end ownership, continuous improvement, testing, monitoring and experimentation.
We aim for teams that are inclusive, helpful, and have a strong sense of ownership for the things they build. Our engineers make some of the most significant decisions for the company and we are looking for bold, open and curious developers.
Want to be part of the change? We're expanding several of our engineering teams, including; teams working on our core checkout product, payment services, fraud prevention, or improving our billing service and shipping credentials to name a few.
What you'll get to do
- Work with increasingly large volumes of data on resilient modern data infrastructure
- Own data products end to end
- Design and implement analytically suitable data structures from complex service data
- Advise upstream/downstream stakeholders on getting the best value out of our data, always with security, compliance, efficiency and standardization at front of mind
- Be an integral part of a team, in addition to its culture and ways of working. Common practices include agile methodologies, pair and mob programming
- Succeed, fail, and learn together with other talented people.
- We believe in an environment that provides an opportunity for growth and see education as an outcome of failure that gets us closer to the next breakthrough
To succeed in this role, we think you should have
- Strong working knowledge in data processing languages like SQLand Python Experience with Spark preferable
- Solid understanding of query and compute engines
- Experience in query design with consideration for platform
- Familiarity with dataset design practices and implementation strategies for multiple use cases (batch based analytics vs streaming)
- Understanding of common analytical practices & methods, and proficiency in one or more languages used by analysts (Python, R, etc.)
- Strong business acumen and product oriented thinking
- Strong communication skills, with emphasis on being able convey technical topics to differing levels of understanding and work closely on common problems with analyst and data science counterparts, in English
- A burning curiosity to learn, own, relay and leverage the stories told by our data
Some technologies you'll get to work with
- Data processing languages: SQL, Python, Pyspark
- Analytical tooling such as Jupyter Notebooks.AWS (Redshift, S3, Glue, EMR)
- Data ingestion and streaming tools such as Kafka, Flink, Kinesis Firehose, Apache Airflow