Data Engineer in Data Product Engineering

Schibsted News Media AB; Stockholms kommun; Hybrid; SEK 600,000 - 750,000; Full time

Benefits offered by this job

Flexible working hours

Hybrid work options

Strong learning culture

Job summary

Schibsted News Media AB is looking for a Data Engineer to join their Data & AI organization in Stockholm. You will help build reliable and scalable data solutions that support analytics, reporting, and future AI capabilities across Schibsted Media.

If you enjoy transforming messy problems into maintainable solutions and are willing to collaborate with stakeholders, this role offers a flexible work environment and opportunities for continuous learning and development.

Qualifications

• 3+ years experience as a Data Engineer, Analytics Engineer, or similar role.
• Experience with modern data transformation tools such as dbt and Airflow.
• Experience building data models for analytics, reporting, or product use cases.

Responsibilities

• Collaborate with stakeholders to deliver pragmatic data solutions.
• Design, build, and maintain data pipelines using Snowflake, dbt, and Airflow.
• Contribute to data governance and engineering best practices.

Skills

Strong SQL skills

Data warehousing concepts

Data pipeline building

Data modeling for analytics

Collaboration with stakeholders

Tools

dbt

Airflow

Snowflake

Job description

Join the Data & AI journey at Schibsted Media

Data and AI are becoming increasingly important in how we build better products, support smarter decisions, and create value across Schibsted Media. We are looking for a Data Engineer who wants to help build reliable, scalable, and well-governed data products used across our media brands.

In this role, you will work at the intersection of data engineering, analytics engineering, and platform thinking. You will help us build trusted data models, improve data pipelines, and collaborate closely with stakeholders across Finance, HR, Product, Subscription, and other Data & AI teams.

You will join the Data & AI organization in the Data Product Engineering team, where we build data capabilities that help teams across Schibsted Media make better decisions, create trusted data products, and enable future AI use cases.

About the role

We are looking for someone who enjoys building solid data solutions and working closely with others to turn business needs into useful, maintainable data products.

You do not need to have all the answers, but you should be curious, structured, and willing to take ownership of your work. You will contribute to how we build data as a product, including creating data models that are reliable, well-documented, and designed for real use cases, not just pipelines that move data.

As part of a newly formed team of Data / Analytics Engineers, you will work with fellow data engineers, collaborate with adjacent teams, and help improve our engineering practices over time. You'll have the opportunity to influence how we work, shape our engineering culture, and make a real impact from day one. We're now looking for 2-3 more engineers to join us on the journey.

What you will do

• Collaborate with stakeholders to understand needs, clarify requirements, and deliver pragmatic data solutions
• Design, build, and maintain data pipelines using technologies such as Snowflake, dbt, and Airflow
• Develop maintainable data models that support analytics, reporting, and AI use cases
• Contribute to good practices for data modeling, transformation, testing, documentation, and governance
• Work with other Data & AI teams to align on platform capabilities, standards, and shared ways of working
• Help improve reliability, performance, cost-efficiency, and scalability of our data solutions
• Participate in code reviews, technical discussions, and continuous improvement of our ways of working
• Contribute to a culture of ownership, learning, and collaboration

What we are looking for

Must have

• 3+ years experience as a Data Engineer, Analytics Engineer, or similar role
• Strong SQL skills and good understanding of data warehousing concepts
• Experience building data pipelines or data models for analytics, reporting, or product use cases
• Experience with modern data transformation or orchestration tools, such as dbt, Airflow, or similar
• Ability to take ownership of tasks and deliver maintainable solutions
• Good communication skills and ability to work with both technical and non-technical stakeholders. English is our main working language.
• Collaborative mindset and willingness to learn from and contribute to the team

Nice to have

• Experience with Python or scripting for data engineering workflows
• Experience with Snowflake, dbt, Airflow, or similar tools
• Experience with CI/CD, version control, and engineering best practices
• Experience with cloud platforms such as AWS, GCP, or Azure
• Interest in data quality, observability, governance, or access control
• Experience working in a cross-functional or product-oriented environment

Why join us?

Opportunity to build trusted data products with real impact across Schibsted Media.

A role with ownership, learning opportunities, and support from experienced colleagues.

Flexible working hours and hybrid work options with strong trust and autonomy.

International environment with offices in Oslo, Stockholm, and Krakow.

Strong learning culture with learning budget and active engineering & AI communities.

Access to Schibsted's media products, including premium news and podcasts.

About you

You enjoy turning messy problems into clear, maintainable solutions. You care about technical quality, but you also understand that good engineering is about tradeoffs, communication, and delivering value.

You are comfortable asking questions, learning from others, and taking responsibility for your work. You like collaborating with stakeholders and teammates, and you want to grow as an engineer while contributing to data products that are useful, trusted, and impactful.

If you want to help build trusted data products that enable better decisions and future AI capabilities across Schibsted Media, we would love to hear from you.