データエンジニア/ Senior Data Engineer
Cognite
Japan (Tokyo)
What Cognite is:Relentlessto 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 heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements.
We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not backwards - you’ll feel right at home here.
Our Moonshot is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future.
How you’ll demonstrate Ownership
Define queries alongside Subject Matter Experts (SMEs) based on an understanding of client requirements. Develop custom extractors using backend technologies and languages (Python,Spark, Rest API, etc.). Customize existing extractors (e.g., database extractors using SQL, event streaming with Kafka) and deploy using Docker. Create custom data models for data discovery, mapping, and cleansing. Collaborate with product development teams to translate customer needs into future product features. Prototype data visualizations and dashboards.The Impact you bring to Cognite
Knowledge, aptitude, and passion for Data Engineering and AI technology. English proficiency: Reading/writing level or higher (must be proactive about verbal communication). Professional coding experience in Python. Strong communication skills with both customers and internal team members. Preferred Domain Knowledge: Experience with operational data and business drivers in heavy industries. Education: Bachelor’s degree (required); Master’s degree preferred. Consulting Ability: Experience negotiating requirements confidently with customers and peers. Integration Design: Experience in enterprise integration, CRM, or IT integration design. Project Leadership: Experience leading implementation in data and analytics projects. Technical Breadth: Broad experience across the data and analytics stack. BI Tools: Proficiency in Business Intelligence tools and enterprise analytics (e.g.,Power BI). Data Tools: Proficiency in SQL and Big Data tools (e.g., Apache Spark ecosystem). Cloud Experience: Experience with public clouds (AWS, GCP, or Azure—Azure preferred), including network security, IDPs, and application hosting. Operations: Experience in support and change management; designing architectures for centralized monitoring, logging, and reporting. DevOps Mindset: Familiarity with Git, CI/CD, and deployment environments. Technical Background: Willingness and ability to write code for advanced topics when necessary. Architectural Skills: Skills in data modeling and infrastructure solutions (e.g.,Data Warehouse, Big Data architecture). Industry Tech: Familiarity with industrial equipment lifecycles, Data Lakes/Lakehouses, DataOps, and GenAI. Stakeholder Management: Success in coordinating across diverse stakeholders (IT/DX teams, plant managers, engineering depts) from initial pilot to enterprise-wide scale. Startup Experience: Experience in Series A, B, or C startups.
- Impact 2025
- Cognite's Industrial AI: Moonshot
- We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.
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