Data Engineer - Pulse - Summer Internship

Are you an aspiring programmer willing to work on real production-ready projects and develop your skills with support from experienced developers? If your answer is yes, we invite you to apply for the summer internship program at Schibsted! We are opening our doors to students who want to gain hands-on experience and practice their skills!

Based on your performance we might offer you part-time employment for the time of your studies after the internship. Take the chance!

What will you do

• You will join us for 2 months (June-July) on a full-time basis – the internship is paid
• You will join our team as a full team member, participating in our ongoing projects and tasks. You will either get your own tasks or pair up with a senior team member so you can deliver code to production, contributing to the team’s goals and objectives
• You will get assigned an intern buddy who will support you through the whole eight weeks of your internship
• You will be able to use technologies you know in real-life projects and you will also play with exciting technology which may be new to you
• You will work together with experienced developers, your intern buddy, as well as get to know more about the agile product development cycle
• At the end of the internship period, you will share a summary of what you have done and learned, and also potential improvements and findings

About you

• You want to know what Data Engineering is like for real
• You feel comfortable writing computer programs and have some experience with source control tools like git
• You are a 3rd to 5th-year student
• You have good English skills and are comfortable using it on a daily basis
• You are eager to learn and share

To get the most out of your time with us, we expect you to be proactive in your own development. We want to hear your ideas, so be ready to have an opinion and speak up from day one. Furthermore, you are driven and enjoy collaborating in a team. About the Management and Distribution team.

The team

Our team is responsible for Pulse - Schibsted’s biggest event streaming platform. We currently both stream events and store some of them in a data lake. Each day the streaming pipeline receives 1.6 billion events from newspapers and marketplaces such as VG, Aftonbladet, and FINN. These events are filtered, transformed, and enriched in near real time. Then they are streamed to external repositories so that data analysts can extract value from the data. In addition, we make sure that data is processed in accordance with the privacy preferences of the users and that they can exercise their rights to be forgotten or audit their data as established by GDPR.

Our day-to-day consists of developing and maintaining Pulse as the most powerful and reliable internal platform for everybody at Schibsted to collect and distribute millions of their events every day. In an environment of constant change, we too must constantly improve and upgrade our tech and features while maintaining stability for our users. This translates to a decent amount of maintenance work (upgrading library versions, scaling infrastructure, migrating to new monitoring or logging solutions, reducing our release times) and a lot of discovery work for how to make our product even more powerful and efficient (working with the product team to discover new features our customers need, figuring out the optimal use of new technologies available in AWS, adding new ways of integrating with our platform, adding more automation to commonly repeated tasks, optimizing our resource usage and re-evaluating our tech stack).

• Our tech stack consists of (don’t worry if you are not fluent with any of these – we will teach you!)
• Scala is our main programming language (if you know Java - you’ll love learning Scala ;) ). We also have some small elements of Java and Python.
• AWS is our cloud provider of choice. Services we use include:
• S3
• EC2 and EKS
• Kinesis
• EMR
• CloudFormation
• Apache Kafka for all our streaming needs (and we have a lot of those)
• Apache Spark for our batch jobs (both production and ad hoc analysis)
• Luigi for scheduling batch jobs