Role & responsibilities

As a Data Modeller working with Cognite Data Fusion, you design and maintain the semantic layer that turns raw industrial data into structured, queryable, and AI-ready knowledge: Core Technical Duties (CDF-Specific) - Design, develop, and evolve semantic data models in CDF using Containers, Views, and the Data Modeling Service (DMS). - Extend and customize the Enterprise Data Model (EDM) to fit TotalEnergies upstream domain needs (assets, wells, equipment, time-series, events, documents, etc.). - Build and maintain asset hierarchies, relationships, and contextualization rules between different data sources. - Collaborate with domain experts to translate complex upstream business concepts (drilling, production, reservoir, maintenance) into expressive and scalable data models. - Define reusable Views for different use cases (operational dashboards, predictive analytics, digital twins, AI agents). - Ensure models support high performance for GraphQL and REST queries, time-series integration, and file/object linking. - Manage model versioning, deployment across environments (Dev/Test/Prod), and integration with CI/CD pipelines. - Implement data governance aspects within models: metadata, lineage, access controls, and quality rules. Transversal / Senior-Level Duties - Provide technical leadership on data modeling best practices and standards across squads and the wider upstream digital community. - Work closely with Data Engineers (on ingestion & extractors), DevOps (on model deployment automation), and Solution Builders (on consumption layers).



- Support the industrialization of use cases such as predictive maintenance, real-time optimization, safety applications, and emissions monitoring. - Conduct model reviews, performance optimization, and debugging of complex queries. - Stay current with CDF data modeling capabilities and contribute to Communities of Practice (CoP). The emphasis is on creating flexible, extensible models that accelerate solution delivery while maintaining consistency and scalability across global assets.

Preferred candidate profile

Technical Skills - Deep expertise in Cognite Data Modeling concepts: Spaces, Containers, Views, Instances, GraphQL schema, and the Core Data Model (CDM). - Proficiency with industrial data types: time-series, asset hierarchies, events, 3D/files, and contextualization. - Experience designing scalable knowledge graphs and semantic models for digital twins. - Good knowledge of Python (CDF SDK), SQL, and GraphQL for modeling and querying. - Understanding of CI/CD for data models and DataOps practices. - Familiarity with related tools: data lineage, metadata management, and integration with Azure or other clouds. Soft & Additional Skills - Excellent ability to collaborate with both technical teams and domain experts (bridge business and technology). - Robust analytical and abstraction skills to model complex industrial processes. - Agile mindset and experience working in cross-functional squads. - Languages: English is mandatory; French is a strong advantage for Paris-based or headquarters roles. Cognite Data Fusion (CDF), Microsoft Azure, Databricks

📌 Data Modeller (Bengaluru)
🏢 Larsen and Toubro (L&T)
📍 Bengaluru