Job Opportunities API

Join the Data & AI journey at Schibsted Media Data and AI are becoming increasingly important in how we build better products, support smarter decisions, and create value across Schibsted Media. We're looking for a Data Engineer to join our Data Infrastructure team and help build the shared data platform that powers analytics and AI across Schibsted Media. Our team enables data teams to build trusted, scalable, and well-governed data products. In this role, you will work at the intersection of data engineering and platform engineering. You'll help improve our data platform while also contributing to trusted data models, modern data pipelines, and engineering practices used across the organization. You will join the Data & AI organization, where we build data capabilities that help teams across Schibsted Media make better decisions, create trusted data products, and enable future AI use cases. About the role We're looking for someone with 4+ years of experience who enjoys building solid data solutions while improving the shared data platform that enables teams across Schibsted Media. You'll work with technologies such as Snowflake, dbt, Airflow, and Python to develop shared tooling, maintain platform capabilities, and contribute to modern data engineering practices. You'll also help deploy and manage cloud infrastructure, automate operational tasks, and continuously improve the reliability and scalability of our platform. While prior infrastructure experience is a plus, we're looking for someone who is eager to learn and grow in this area. What you'll do Collaborate with Data & AI teams to understand platform needs and deliver scalable data solutions Design, build, and improve shared data platform capabilities, developer tooling, data pipelines, and automation using technologies such as Snowflake, dbt, Airflow, and Python Support and evolve our Privacy Compliance Platform, helping enable secure, compliant, and governed access to data across Schibsted Media Deploy, maintain, and improve cloud infrastructure using Infrastructure as Code and modern automation practices Improve reliability, observability, performance, cost-efficiency, and scalability of our data platform Develop reusable templates, tooling, and documentation that enable self-service across Data & AI teams Develop maintainable data models that support analytics, reporting, and AI use cases Contribute to good practices for data modeling, transformation, testing, documentation, and governance Participate in code reviews, technical discussions, and continuous improvement of our ways of working Contribute to a culture of ownership, learning, and collaboration What we're looking for Must have 4+ years of experience as a Data Engineer or similar role Strong SQL skills and a good understanding of modern data warehousing concepts Experience building data pipelines and working with orchestration tools such as Airflow or similar Hands-on experience with dbt and modern data transformation practices Experience with Python for data engineering or automation Experience with Git and modern software engineering practices Ability to take ownership of tasks and deliver maintainable solutions Good communication skills and ability to work with both technical and non-technical stakeholders. English is our main working language. Collaborative mindset and willingness to learn from and contribute to the team Nice to have Experience with software engineering practices such as automated testing, CI/CD, and code review workflows Experience with Snowflake or similar cloud data platforms Experience with Infrastructure as Code (Terraform or similar) Experience with AWS, GCP, or Azure Interest in data quality, observability, governance, or platform engineering Why jo