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Senior Data Engineer at Cognite (Oslo) building production-grade data pipelines and infrastructure for industrial customers using SQL, Python/Java, REST APIs, Kubernetes, and GCP/Azure. A customer-facing role that also involves data modeling, cross-functional collaboration, and mentoring junior engineers.
Data engineer at Cognite (industrial AI) designing and building data pipelines and custom extractors with Python, Spark, SQL, Kafka, and Docker to centralize and curate client data for their AI product suite. Hybrid role based out of the Houston office, working directly with O&G/manufacturing clients.
Design and build scalable data pipelines for industrial AI platforms, integrating oil & gas and manufacturing data using Python, SQL, and cloud services to enable smarter operations.
Builds and optimizes Cognite’s Enterprise Data Warehouse (EDW) for FP&A, designing semantic layers, pipelines, and AI-driven reporting to empower business decisions using Azure, Fabric, and Power BI.
Data Engineer building customer-facing data solutions on Cognite Data Fusion, the company's industrial DataOps/AI platform, for clients in energy, power & utilities, and manufacturing. Day to day: designing data pipelines, integrations, and custom data models using SQL, Python/Java, REST APIs, Kubernetes, and GCP/Azure.
Data Engineer II at Cognite designs and builds scalable data pipelines, integrations, and data models on the Cognite Data Fusion industrial DataOps platform, serving customers in Oil & Gas, Power & Utilities, Energy, and Manufacturing. Core stack: Python, SQL, Java, REST APIs, Kubernetes, GCP/Azure, and Git/CI-CD.
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