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Principal Solutions Consultant for Cognite’s industrial AI platform, guiding pharma/life sciences clients through technical adoption, solution architecture, and enterprise-scale deployments using Python, cloud platforms, and industrial data integration.
What Cognite is: Relentless to achieve Cognite operates at the forefront of industrial digitalization, building AI , and data solutions that solve the world’s hardest, highest-impact problems. With unmatched industrial…
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.
Leads end-to-end delivery of complex Industrial AI implementation projects for large industrial customers — from contract signing through deployment, adoption, and value realisation — owning scope, schedule, budget, and stakeholder management. Requires technical fluency with cloud, APIs, and data systems plus industrial-sector experience.
Design and lead AI-driven industrial data solutions for energy and manufacturing customers, integrating cloud platforms and Python/Java to improve efficiency and sustainability.
Directs global compensation and benefits strategy, designing scalable pay frameworks and equity programs to attract and retain AI/industry talent while ensuring compliance and alignment with Cognite’s industrial AI growth.
Build and operate a serverless execution engine and workflows orchestration layer for industrial AI, ensuring reliability, scalability, and observability for Fortune 500 clients.
Principal Field Engineer builds and prototypes industrial AI solutions for oil & gas clients using Cognite Atlas AI™ and Data Fusion®, bridging technical and business needs.
Senior Database Reliability Engineer owning the reliability, automation, and scalability of Cognite's core data infrastructure: a 1000+ instance PostgreSQL fleet, Elasticsearch clusters, and Kafka streaming across Azure, AWS, and GCP on Kubernetes. Core stack is PostgreSQL, Elasticsearch, Kafka, Kubernetes, and Terraform, with automation in Go or Python.
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.
Principal Full Stack Engineer at Cognite architecting and building the Cognite Data Fusion® industrial data platform—both frontend and backend—using Kotlin/Java/Python/Rust, modern JS/TS (React/Angular/Vue), cloud services (AWS/GCP/Azure), and Kubernetes.
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.
Academy Engineer at Cognite builds and delivers technical training for its industrial AI platform, Cognite Data Fusion. Day to day: creating courses, hands-on labs, and e-learning, and delivering instructor-led training to customers and partners as a technical SME. Core stack: Python, SQL, Azure, DataOps, plus tools like Articulate Rise and Synthesia.
Customer-facing Senior Solutions Architect at Cognite (industrial AI/data platform) who designs end-to-end solutions, integrations, data models and ingestion pipelines for large process and energy industry customers. Hands-on with Python, SQL, Java, REST APIs, data connectors and cloud platforms (Azure, AWS, Google).
Solution Architect designing end-to-end industrial AI and data solutions using Cognite Data Fusion. The role involves technical consulting, data modeling, and integration design using Python, SQL, and cloud platforms (AWS/GCP/Azure) to solve complex problems for heavy asset industries.
Software Engineer building serverless execution engines and workflow orchestration for an industrial AI platform. Responsibilities include designing REST/event-driven APIs, ensuring scalability across multi-cloud environments (Azure, GCP, AWS), and implementing observability using Open-telemetry. Core stack: Kotlin, Python, Kubernetes, and Kafka.
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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