About the Role
We're looking for a Data Engineer to join a collaborative, high-performing team in Stockholm.
This role is very hands-on. You'll be working closely with product, analytics, and engineering teams to build and improve the data platform ensuring data is clean, reliable, and actually useful for decision-making.
It's a great fit for someone who enjoys solving real problems, working with modern tools, and being part of a team that values quality and simplicity.
What You'll Be Doing
* Designing, building, and maintaining scalable data pipelines
* Developing ETL/ELT workflows for both batch and streaming data
* Working with Databricks and Spark to process large datasets efficiently
* Collaborating with cross-functional teams to deliver data solutions that scale
* Writing clean, production-level code in Python and SQL
* Improving data quality, reliability, and performance across the platform
* Supporting best practices in data governance and security
Tech Environment
You'll be working in a modern, cloud-based setup:
* Core: Databricks, Azure, Python, SQL
* Cloud: AWS (preferred), with Azure or GCP as a plus
* Data Engineering: ETL/ELT pipelines, Delta Lake, Airflow (or similar orchestration tools)
* Version Control & CI/CD: Git, Jenkins (or similar)
* Other: APIs, streaming data, and large-scale datasets
What We're Looking For
* 3-5 years' experience as a Data Engineer
* Strong hands-on skills in Python and SQL
* Solid experience with Databricks and Spark
* Proven track record building and optimising data pipelines
* Comfortable working in a Linux or cloud environment
* A proactive, curious mindset-you take ownership and get things done
* Comfortable working onsite in a collaborative team environment
Why This Role
* Immediate impact - you'll be contributing from day one
* Modern tech stack - work with Databricks, AWS, and scalable data systems
* Strong team environment - collaborative, low hierarchy, and delivery-focused
* Interesting challenges - large datasets, real-time data, and performance optimisation
