Data Engineer in Data Product Engineering

About the Position

Build trusted data products used across Schibsted’s leading Nordic media brands. Join a collaborative team in Oslo or Stockholm and shape how data supports smarter decisions.

We usually respond within a week

If you choose to apply, please read the job ad in full and include a short cover letter. We are most interested in hearing from the real you, so we encourage authentic applications written in your own words.

The Opportunity in a Nutshell

Interested in combining hands-on data engineering with close collaboration across the business? This role could be a good fit for someone with 4+ years of experience who enjoys building reliable data products and working with others to make them useful.

Role: Join as a Data Engineer in our Data Product Engineering team within Schibsted's Data & AI organization, where we build reliable, well-governed, and scalable data products used across Finance, HR, Product, Subscription, and other parts of the business.

Core tools and practices: Our everyday toolkit includes SQL and Python as core languages, together with Snowflake, dbt, Airflow, AWS, Terraform, and Git, supported by solid engineering practices around testing, documentation, CI/CD, and version control.

Company: Schibsted is home to some of the most established and widely used media brands in the Nordics, including Aftenposten, VG, Svenska Dagbladet, Aftonbladet, E24, Bergens Tidende, and Stavanger Aftenblad. Across our broader Data & AI focus, data, analytics, and AI help us build better products, support smarter decisions, and create value across those newsrooms and businesses.

Location: This role is based in Oslo or Stockholm. We work in a hybrid setup, which means this is not a fully remote role, and candidates need to reside in Sweden or Norway and be able to work from one of our offices at least 2 days a week.

Why this role: You will join a relatively new team with room to contribute, learn, and help shape how we work as we continue to build trusted data products across Schibsted.

Responsibilities

• Collaborate with stakeholders to translate business needs into pragmatic, well-scoped data solutions.
• Design, build, and maintain reliable pipelines and transformations in Snowflake, dbt, Airflow, and Python.
• Develop scalable data models that support analytics, reporting, and future AI use cases.
• Improve technical quality through testing, documentation, monitoring, and maintainable engineering practices.
• Contribute to good architectural and implementation decisions across the team.
• Contribute through code reviews, pairing, and knowledge sharing within the team.
• Work closely with adjacent platform and Data & AI teams to align on standards, dependencies, and shared ways of working.

Requirements

• Around 4+ years of experience in data engineering or a closely related role, with a track record of building reliable data solutions in production environments.
• Strong SQL skills, along with a solid understanding of data modeling, data warehousing, and how to design data products that are useful, trustworthy, and maintainable.
• Ability to write and debug SQL and Python at a strong professional level. AI-assisted tools are welcome, but this role requires solid enough fundamentals to solve everyday engineering problems without depending totally on them.
• Good software engineering fundamentals, including the ability to structure maintainable applications and apply object-oriented design principles where appropriate.
• Hands-on experience with dbt in production environments and solid working knowledge of the wider toolkit we use, including Airflow, Snowflake, AWS, Terraform, Git, and Python or similar tools.
• Comfortable making pragmatic technical decisions in environments where requirements evolve and not everything is fully defined upfront.
• Care about engineering quality and can contribute to practices around testing, documentation, observability, governance, and cost-efficient pipeline design.
• Clear communication matters just as much as technical strength. Value people who can work well with both technical and non-technical stakeholders, explain tradeoffs clearly, and contribute positively to team collaboration and knowledge sharing.

We Offer

• Join a team that is still shaping its ways of working, which means there is real room to contribute, learn, and grow.
• Work on data products with visible impact across Schibsted, supporting both technical and non-technical users in domains such as Product, Subscription, Finance, and HR.
• Be part of a company whose work matters in everyday life across the Nordics, helping support trusted media brands through better data, analytics, and AI capabilities.
• Work in an international environment with strong trust, autonomy, and good opportunities for learning through engineering communities and collaboration across Data & AI.

About the Company

Schibsted is home to some of the most established and widely used media brands in the Nordics, including Aftenposten, VG, Svenska Dagbladet, Aftonbladet, E24, Bergens Tidende, and Stavanger Aftenblad. Across our broader Data & AI focus, data, analytics, and AI help us build better products, support smarter decisions, and create value across those newsrooms and businesses.

Application Details

The application period closes on 28 September 2026. We review applications on a rolling basis, so we encourage you to apply as soon as possible.

Division: Schibsted

Locations: Oslo, Stockholm

Employment type: Full-time

Apply before: 28 September, 2026

Contact information: Email: [email protected]