Data Engineer: Build the data foundation for the future of care
Sensio · Oslo
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- Company
- Sensio
- Location
- Oslo
- Posted
- June 15, 2026
About this job
We’re looking for a data engineer This role sits in our data platform team and will work across our product, engineering and AI teams. Your responsibility will be to turn data from sensors, applications, and external systems into structured, reliable datasets that can be used across Sensio’s products. In Sensio 365, we have a large and growing range of real-time signals. For example, our RoomMate sensor can register activity patterns, movement, presence, and noise in a resident’s room. Additionally, other Sensio devices, third party devices, and system integrations all contribute alarm and event data. When all this data is processed, structured and combined over time, they can provide much more value for our customers than they do as individual datapoints. This is what enables products such as Sensio Insight to identify patterns, present meaningful information and help care providers better understand resident activity and what enable continuous improvement of the functionality and accuracy of our AI-sensor Roommate. As a data engineer, you will build the processors, datasets and platform services that make this possible. You may receive data through an API, a Kafka message or an existing dataset, and your job will be to determine how it should be interpreted, transformed and stored so that it becomes reliable and useful downstream. At Sensio, you shouldn’t expect to always receive your tasks as fully defined technical specifications. You will work in collaboration with product managers, machine learning engineers and other developers to understand the problem, define the right data structure and decide which processing is required. This is a role for someone who is more interested in understanding the problem than reaching for a predetermined solution. You will help build a platform that supports an increasing number of sensors, data formats and use cases as our ecosystem continues to grow. We are looking for someone who understands that good data engineering is what allows teams to build better models, better products and better decisions. This role will be placed at Sensio’s office in Oslo. You will report to the Dev Lead for Data Platform. Your day-to-day You will contribute to the continued development of Sensio’s data platform and the data services that support products such as RoomMate, Sensio Insight and Sensio 365 more broadly. Your daily work will include: Building data pipelines, processors and services in Python, C# and.NET Receiving data from APIs, Kafka and existing datasets Turning sensor, alarm and activity data into reliable, structured datasets Working with PostgreSQL and large data volumes Collaborating closely with product managers, ML engineers and developers to define the right solutions Improving platform reliability, scalability and secure data handling This is what we’re looking for We are looking for a skilled Data Engineer with strong technical judgement, high standards for data reliability and an understanding of how data supports modern product and ML development. If you’re the right candidate for the job, you probably have: Strong experience with data engineering, backend development or data-heavy platform services Strong C# and.NET skills Experience with PostgreSQL and working with large data volumes Strong understanding of data modelling, data structures and dataset design Experience with data integrations, APIs, Kafka or other event-driven architectures Familiarity with common data and machine learning tools such as Spark, MLflow and PyTorch Your job is to make sure the data is reliable, structured, accessible, traceable and handled responsibly, so that the teams building models and products can move faster and make better decisions. Bonus points if you have experience with one or more of the following: FastAPI, dbt, Alembic or similar tools for building and maintaining data services Multi-modal data, sensor data, image data, telemetry or data from edge devices Kubernetes or cloud-based platform environments
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