Senior Analytics Engineer - Customer and Behavioral Data

Do you want to build the data foundation on which customer experiences, personalization and AI across some of Denmark's strongest media brands will rest?

At JP/Politikens Hus we bring together the work with customer data and behavioral data in a new team under Digital Customer Journeys. The team will deliver credible and well-documented data products that enable Politiken, Jyllands-Posten, Ekstra Bladet and Watch Medier to understand their users and customers and act on the insights.

We are seeking an experienced Senior Analytics Engineer, who can set the direction for how we model customer and behavioral data, and at the same time take on a large portion of the development themselves.

The role

As a Senior Analytics Engineer you translate raw customer- and behavioral data into reliable data models and data products. You will be the link between data engineering and the business and create one common truth, so analysts and decision-makers can find answers themselves.

You will work on a brand new data architecture built according to best practice with Snowflake and dbt Cloud, where a central platform team takes care of the infrastructure. Then you can spend time on good data models and data products.

The data products will be used by analysts, commercial teams, activation platforms and increasingly AI agents. The role includes professional sparring, but not people management.

You will join a professional community with analytics engineers in the house's other departments, where we share knowledge, experiences and common standards.

Your responsibilities

• Design and maintain data models for customer and behavioral data
• Develop robust transformations in dbt from raw data to business-ready data products
• Implement common business logic and key metrics so they are calculated consistently across brands, in accordance with the definitions owned by the business
• Build a semantic layer and contextual data, so both humans and AI agents understand and use data correctly
• Implement and maintain the team's data contracts technically in dbt, including enforced schemas, tests and versioning of models, so the data products are stable and reliable
• Handle real-time processing and calculations of customer and behavioral data on our established event platform based on Kafka
• Contribute to design of events, schemas and entities in our Snowplow setup together with the teams that implement tracking
• Document data models, definitions and lineage, so data products can be found and understood, and contribute to data catalog, naming conventions and standards for good data practice
• Ensure version control, code reviews and CI/CD for the team's code and raise the quality through standards and mentoring less experienced analytics engineers

Your first big tasks

• Prepare behavioral data as a data product, with a consistent data model, documentation, data contract and quality metrics
• Map out what needs to be in place before customer data can be ready as the team's next data product
• Define modeling principles and standards for customer and behavioral data in dbt
• Implement data contracts and quality metrics for the key data products

We imagine that you

• Have several years of experience as an analytics engineer, data engineer or in a similar role focusing on data modeling
• Are very strong in SQL, have solid experience with dimensional modeling and strong analytical and problem-solving abilities
• Have in-depth experience with dbt and a modern cloud data warehouse, preferably Snowflake
• Work in a structured way with Git, pull requests, tests, CI/CD and code review and according to data engineering principles such as modularity and reusability
• Have experience with behavioral data, event data, customer data or identity
• Have knowledge of how data should be served to AI agents, e.g., through semantic layers, rich metadata and context
• Can translate vague business needs into precise definitions and robust data models
• Communicate clearly with both specialists and non-technical colleagues
• Thrive in setting standards and raising the quality of others' work
• Have a pragmatic approach and can balance the right thing with what creates value now

Why you should choose this role

You will have the opportunity to shape a new team from the start and become a key person in building the data foundation on which JP/Politikens Hus's customer experiences, personalization and AI solutions will rest in the coming years. You start on a fresh and modern data architecture, where you help set the standards for how we work in Snowflake and dbt, rather than inheriting them. At the same time you work with large amounts of data and concrete business needs close to product and commercial teams.

You will have substantial influence on standards, models and ways of working and the opportunity to stay close to the technical craft. At the same time you become part of an open and informal workplace with a high degree of freedom and responsibility, professional and social communities, pension and health insurance.

As part of our media house family we can offer a dynamic and inspiring workplace that sits in the midst of a rapid digital development.

Practical

Work location: City Hall Square, Copenhagen

Application deadline: Saturday 31 October 2026

Questions about the role: Data Engineering Manager Lars Gundersen [email protected]

Process: We assess applications and invite to interviews on a rolling basis.

Application deadline: 31 October 2026

Location: JP/Politikens Hus