Schibsted is a growing and diverse family of over 50 brands whose mission is to empower people in their daily lives, and each brand contributes to it in its own way. Amongst our brands, you can find leading Nordic marketplaces like Finn and Blocket, world-class media houses like VG and Aftonbladet (we are the largest media group in Scandinavia), and other rapidly developing digital companies like Prisjakt, Lendo, and many others.
Data Foundations is a central department within Schibsted that is responsible for the data platform and is working on data-fueled products with an emphasis on volume, velocity, and privacy. We are building products at scale, serving the whole of Schibsted and its brands.
Our team within Data Foundations is responsible for making data accessible in Schibsted in a simple, robust, timely, and privacy-compliant way to enable data-driven business decisions. We help data consumers manage access to their behavioral datasets and dispatch events to 3rd party data services to unlock the value of their data with minimum latency. This team manages data for millions of users across Nordic countries!
The Management and Distribution team has a strong soul: we aim to be of service to our stakeholders and teammates, persevere and cooperate when facing challenges, are curious to figure out how stuff works (especially when it doesn’t), and most importantly put our team first by helping each other.
Who are we looking for?
We are looking for a Data Engineer who has completed a few features together with their team and is also respectfully proactive in taking ownership of and investigating the “why’s”, of things.
- You would be working on functionality for a product that is at the core of Schibsted and used in the majority of brands like Finn, Blocket, VG, or Aftonbladet - setting the direction together with the brands and the product manager. For example:
- Engineering and implementing highly scalable systems and data pipelines for the Schibsted data management platform, both for real-time and batch processing - always working in pairs
- Ensuring compliance with data governance, security policies, and privacy laws for storage of, and access to, personal data
- Monitoring and optimization of data pipelines
If you also enjoy working in a team where teammates express their thought processes around tasks clearly, and share and receive constructive feedback on their work to both increase the quality of their work but also grow professionally, then you might be our new teammate!
- Knowledge of, or some experience with developing services and applications on, cloud solutions such as AWS, Azure, or GCP
- Currently, we have most of our services running on the JVM with the main programming language being Scala in the team - being familiar with and able to code using a JVM language (Kotlin/Java/Scala) is needed
- A Bachelor’s degree or higher in Computer Science, Informatics, Applied Mathematics, Statistics, any quantitative field, or relevant work experience
Nice to haves
- Knowledge of, or some hands-on experience with, some of the state-of-the-art big data technologies, such as Kafka, Spark, Flink, Hadoop, Storm, and Cassandra
- Interest in having an impact in our organization by keeping cross-team dependencies and relationships in mind when engineering solutions
- Familiarity with DevOps, concurrent/multithreaded programming, or distributed systems are all advantageous
What is our technology stack?
- AWS for storage and other infrastructure (S3, Kinesis, EC2, EMR, Cloudformation, ...)
- Scala for most of our services, and a little Python and Java too
- Kafka for stream processing and Spark for batch processing
As a part of Schibsted, you will also have the opportunity to share knowledge and learn from other data engineers across the organization. We encourage a diverse, collaborative, and creative work environment, where you will develop and push for state-of-the-art solutions in big data processing as well as building reliable and highly scalable services.
A little peek at what we offer
- Internal career growth opportunities
- The flexibility of working from home
- Excellent work equipment of choice at home and at the office
- Central office locations
- Opportunity for development of competencies, conferences, and various knowledge-sharing events such as hackathons, innovation days, etc.
- Mentoring, since we have many senior engineers in the team and the department
- 2 lab days every month to explore new technologies and development ideas connected to our work
- Opportunity to take on various learning courses and classes through our Schibsted Learning Lab and LinkedIn Learning
- Pension scheme
- Schibsted share saving and matching plans
- Wellness programs (e.g. running, yoga, classes with a coach...etc.)
Our Interview process
- Recruiter screening (30 min): An initial call with a talent acquisition partner. We’ll tell you a bit about us, answer any questions you may have, learn about your background and what you’re looking to do
- Home assessment and code review (60 min) or a live coding interview: a take-home exercise with follow-up discussion where you meet two of our engineers, or a live coding interview (Scala, Java, Python)
- System design interview (60 min) : System Design interview and potentially some computer science fundamentals discussions with two engineers
- Values interview (30 min): meeting the Engineering Manager and Product Manager of the team for a short discussion
- Offer extended! If you are interested in talking to more potential coworkers or have additional questions, we will also arrange any additional chats for you!