Job Description
We are looking for a Data Engineer to build and run the data platform behind our
analytics and machine learning work, based in Stockholm with a hybrid setup.
You will design and maintain the pipelines that move data from our production systems and
third-party sources into the warehouse, keep them reliable, and make the data usable for
analysts and data scientists. That means modelling, testing, monitoring, and a fair
amount of talking to the people who produce the data and the people who consume it.
You join a data team of five, working closely with backend engineering and the analytics
team. The stack is Python, SQL, dbt and Airflow on top of BigQuery, running in GCP. We
are not dogmatic about tools, but we care a lot about data that can be trusted.
This is a hands-on role for someone who has run pipelines in production before and has
opinions about how to do it well.
Skills & Requirements
3+ years as a data engineer or in a similar role, with pipelines running in production
Strong SQL and Python
Experience with a modern data stack: dbt, Airflow or similar orchestration, and a cloud
warehouse such as BigQuery, Snowflake or Redshift
Data modelling for analytics, including dimensional modelling
Experience with a cloud platform, GCP preferred
Familiarity with data quality testing and monitoring
Fluent English
Experience with Kafka or other streaming systems is a plus
Experience with Terraform or infrastructure as code is a plus
About the company
Demo account
