SchibstedAnalytics and Data Engineer
Schibsted is hiring an Analytics and Data Engineer in Oslo, Norway. Level rates it ; you can apply on Schibsted.
Level's read on this job
- On Level's scale, this data engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include Snowflake, dbt and Sanity.
- Level classifies it as a mid-level role.
- Level lists 40 other open roles at Schibsted.
- The role was posted in the last few days.
AI in this role
Analytics and Data Engineer to build pipelines and statistical models for affiliate marketing data, utilizing LLMs for data classification.
About Schibsted Marketing Services
Schibsted Marketing Services is Schibsted´s advertising organization, representing some of the strongest news brands in Norway and Sweden - like VG, Aftonbladet, Aftenposten and SvD.
Advertising plays a central role in funding independent news media, and affiliate marketing is a growing component of our advertising revenue. We are currently increasing our focus on affiliate marketing and ecommerce, and are looking for a analytics and data engineer to work on performance data pipeline and analytics. Affiliate is a cross brand initiative in Schibsted for monetization across most of our brands in Norway and Sweden.
About the Role
As an Analytics and Data Engineer on Affiliate your task is to define data structures and pipelines that fuels reporting, ad hoc analytics as well as content distribution and content ranking. For the right profile working on statistical models for estimation and forecasting of expected revenue of click or article view can be a part of the scope.
This role will involve a lot of content data and unique problem solving associated with that. One example of this is setting up content databases and integrations for current offers, setting up integrations for our front ends and interacting with our ranking technologies.
Most of the data will flow to or from known standard integrations (Snowflake, Postgres, S3, REST APIs etc), but some data ingestion might involve web crawling and use LLMs for classification. For data exports setting up and maintaining internal APIs might be necessary.
You will work within Ads Data Capabilities and work closely with the affiliate team and with other data teams in Schibsted.
In this role, you will
Develop data pipelines for revenue, click and content data for affiliate
Own data products for affiliate data, as well as semantic layers
Collaborate with our data teams to ensure affiliate distribution gets powered by the data available within Schibsted
Collaborate with our data teams to ensure all advertising can be powered with data generated by affiliate initiatives
Our typical stack
We expect most of the work to be on select technologies already widely used in Schibsted:
Snowflake
DBT
Sanity (as content database)
Airflow
Spark
AWS RDS (PostgreSQL)
We encourage agentic engineering and integrating AI tools into your development workflow.
Requirements
A degree in computer science, data engineering or similar
3+ years of experience in data engineering, analytics engineering or a closely related field
High level proficiency in Python and SQL
Hands on experience with the technologies in our stack or similar technologies
Knowledge and further curiosity about agentic engineering and AI tooling for coding
Norwegian work permit
Valued skills and experience
Fluency in a Scandinavian language
Experience with performance marketing or other advertising technologies
Experience from media or advertising industry
Proficiency in other programming languages such as Java, Scala or Go
Apply for this position by sharing your CV with us and a few lines about what you like working on. Interviews will take place on an ongoing basis. CV and application text can be in English or any of the Scandinavian languages.
How we rate this
Analytics and Data Engineer at Schibsted rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- Typical data engineer job
- $145k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- What's a project where you used Snowflake hands-on?
- Walk me through how you've used dbt in your day-to-day work.
- What are the limits of Sanity that you've run into, and how did you work around them?
- What's a project where you used Airflow hands-on?
- Walk me through how you've used Spark in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Snowflake, dbt, Sanity, Airflow, and Spark. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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