Data Engineer

emagine; Stockholms kommun; Remote; SEK 650,000 - 950,000; Full time

Job summary

emagine is seeking a Data Engineer for our client in Stockholm to help build a scalable, self-service analytics platform and maintain a robust data infra.

You will own ingestion pipelines, collaborate with data scientists, and develop tools for production-ready data solutions, with emphasis on reliability, observability, and performance.

Qualifications

• Hands-on experience building, scaling, and operating production-grade data platforms.
• 3+ years in data engineering with pipelines, orchestration, and cloud data services.
• Experience with Airflow and large data sets, ETL, and data warehousing on cloud.

Responsibilities

• Maintain and improve ingestion pipelines delivering billions of events daily.
• Support teams in building and optimizing complex pipelines.
• Collaborate to identify pain points and improve the platform.
• Develop new tools and frameworks for the data platform.
• Work with data scientists/analysts to productionize analytics.
• Contribute to ML platform and streaming use cases.
• Establish best practices for software and data development.

Skills

Data engineering

Airflow

Large data sets

ETL pipelines

Cloud platforms

Spark (Scala/Python)

CI/CD (Jenkins, Git)

Software engineering practices

Problem solving

Initiative

Tools

Jenkins

Git

Kubernetes

BigQuery

Redshift

Kafka

Job description

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