Data Engineer
emagine · Stockholm Metropolitan Area, Sweden ·
- Work mode
- Hybrid
- Category
- Data engineering
- Experience
- 3+ years
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The Data Engineer will build and maintain a scalable, self-service analytics platform by managing ingestion pipelines, developing data tools, and supporting ML and streaming projects. The role requires strong expertise in Spark, Python, Scala, and cloud-based data infrastructure.
emagine is looking for a data engineer for our client in Stockholm
Workload: 100%
Location: Stockholm or remote
Duration: Asap - 2027-06-30
As a Data Engineer, you will play an important role in the Data infrastructure team, which is responsible for building and maintaining a scalable, robust, self-service analytics platform.
What you'll do:
Maintaining and improving the ingestion pipeline to reliably deliver billions of events daily in a defined SLA
Provide support for all teams in building and optimizing their complex pipelines
Work closely with other teams to identify pain points and problems around the platform
Develop new tools and frameworks to improve the data platform
Work in close collaboration with data scientists and data analysts to help support their work in production
Work with vast projects such as building an ML platform and streaming use cases
Set up best practices and processes around software and data development
What you bring in:
3+ years of experience in data engineering
Experience working with an orchestration tool (ex, Airflow)
Experience working with a large data set
Experience building complex ETL pipelines
Experience working with cloud providers such as GCP, AWS, or Azure
Strong programming skills in Spark with Scala and Python
Experience working with CI/CD tools like Jenkins and Git
Strong understanding of Software Engineering practices and principles
Excellent problem-solving and communication skills
Self-motivated and have a proven ability to take the initiative to own the problems that come up and solve them
MUST-HAVE EXPERIENCE:
Hands-on experience building, scaling, and operating production-grade data platforms or data infrastructure, including reliability, observability, performance, and self-service capabilities.
It would be great if you also have:
Working with messaging systems like Kafka
Knowledge of Kubernetes
Hands-on experience with any streaming platform
Experience managing a data warehouse in BigQuery or Redshift