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Schibsted Marketing Services in Norway is seeking an Analytics and Data Engineer to define data structures and pipelines that fuel reporting, ad hoc analytics, content distribution and ranking for Affiliate across Schibsted brands.
You will work with Snowflake, DBT, Sanity, Airflow, Spark and AWS RDS, building data products and semantic layers, collaborating with our data teams to empower affiliate distribution and advertising with reliable data.
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.
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.
We expect most of the work to be on select technologies already widely used in Schibsted:
We encourage agentic engineering and integrating AI tools into your development workflow.