Our mission

Empower data teams to work with confidence, precision, and joy by bringing software engineering excellence to data transformation. We create intuitive tools that make pipeline maintenance efficient and cost-effective at any scale. As your data platform evolves with changing business needs, our solutions ensure you can adapt and expand without breaking existing systems, turning data engineers from troubleshooters into strategic innovators who drive business value.

Founders

Øyvind Raddum Berg

Founder & CTO

Øyvind brings over a decade of expertise in systems development with a deep focus on functional programming principles and database technologies. His background in software architecture spans fintech, telecommunications, and ad-tech sectors, where he consistently delivered robust, maintainable systems. Frustrated by the limitations of existing data transformation tools, Øyvind applied his functional programming expertise to reimagine how data platforms could operate with the reliability and confidence of well-engineered software systems. With a Master's in Computer Science from the University of Oslo, he combines theoretical rigor with practical engineering to ensure Datoria's solutions evolve data pipelines from fragile maintenance burdens into strategic assets.

Ingar Abrahamsen

Founder & CEO

Ingar has spent over 10 years specializing in DataOps and large-scale data management across diverse industries. His hands-on experience building and optimizing data infrastructures—both on-premises and in the cloud—that process petabytes of data has given him unique insight into the real-world challenges data teams face daily. At multiple organizations, Ingar has led comprehensive data pipeline rewrites and developed open-source data transformation tools when existing solutions fell short. With his background in Electrical and Electronic Engineering, he brings a problem-solving approach that balances technical excellence with practical business needs, ensuring Datoria's solutions scale effortlessly while remaining intuitive for data practitioners who need to focus on innovation, not maintenance.