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Cognite operates at the forefront of industrial digitalization, building AI and data solutions that solve some of the world’s hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements.
Our moonshot is bold: unlock $100B in customer value by 2035 and redefine how global industry works.
What Cognite is Relentless to achieve
We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not step back - you’ll feel at home here. Join us in this venture where AI and data meet ingenuity, and together, we forge the path to a smarter, more connected industrial future.
How you’ll demonstrate Ownership
- Lead the design and implementation of scalable and efficient data engineering solutions using our platform Cognite Data Fusion®.
- Drive and manage integrations, extractions, data modeling, and analysis using Cognite data connectors and SQL, Python/Java and Rest APIs.
- Create custom data models for data discovery, mapping, and cleansing.
- Collaborate with data scientists, project managers and solution architects engineers on project deliveries to enable our customers to achieve the full potential of our industrial dataops platform.
- Conduct code reviews and implement best practices to ensure high-quality and maintainable code and deliveries.
- Support customers and partners in conducting data engineering tasks with Cognite products.
- Contribute to the development of Cognite’s official tools and SDKs.
- Collaborate with our Engineering and Product Management teams to turn customer needs into a prioritized pipeline of product offerings.
The Impact you bring to Cognite
- Have a DevOps mindset, and experience with Git, CI/CD, deployment environments
- Enjoys working in cross-functional teams
- Able to independently investigate and solve problems
- Humility to ask for help and enjoy sharing knowledge with others
- Minimum 3-5 years of relevant experience in a customer-facing Data intense role
- Experience delivering production-grade data pipelines using e.g. Python, SQL and Rest APIs
- Experience with distributed computing such as Kubernetes and managed cloud services such as GCP and/or Azure
Preferred Experience
- Bachelor or Master degree in computer science or similar. Relevant experience can compensate for formal education
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