Data Engineer in Data Product Engineering

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.

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.

We are looking for someone with a solid foundation in data engineering who is also excited by the opportunity to keep learning,

deepen their craft, and grow together with the team.

• You have 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 are important, along with a solid understanding of data modeling, data warehousing, and how to design data

products that are useful, trustworthy, and maintainable.

• You can write and debug SQL and Python yourself 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.

• On the Python side, we are looking for good software engineering fundamentals, including the ability to structure maintainable

applications and apply object-oriented design principles where appropriate.

• You have 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 and / or similar tools.

• You will likely enjoy this role if you are comfortable making pragmatic technical decisions in environments where requirements

evolve and not everything is fully defined upfront.

• You 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. We 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.

As a Data Engineer, your job is to help us build data as a product, not just pipelines that move data from one place to another.

You will create robust data models, improve the reliability and scalability of our pipelines, and help shape the engineering

practices that make our data products trusted and reusable across Schibsted Media.

Success in this role means growing into a confident contributor who understands our data landscape, ways of working, and

stakeholder needs. Over time, that includes contributing across a mix of smaller support tasks through our weekly rotation as well

as larger pieces of work, helping build reliable pipelines and data models, and developing the judgment to deliver pragmatic

solutions together with the team. Depending on your experience and the needs of the work, that can mean contributing as part of a

team or taking the lead on a project.

• You will 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.

• You will 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.

• You will work in an international environment with strong trust, autonomy, and good opportunities for learning through

engineering communities and collaboration across Data & AI.

• You will join a team that enjoys solving challenging problems, wants to build high-quality data products, and cares about the

people they work with.

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.