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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and implementing industrial data solutions for Oil & Gas operations, with a strong focus on Cognite Data Fusion, data modeling, and integration strategies. Proficient in Python and SQL, with a solid understanding of cloud architecture and deployment practices.
Highest-signal resume keywords
Cognite Data Fusion ImplementationData Modeling and TransformationsPython ProgrammingSQL ProficiencyIndustrial Data Integration Experience
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ModelingData IntegrationContextualizationAPI DevelopmentCognite SDKCloud ArchitectureIdentity StrategiesDeployment PatternsDiagram ContextualizationIndustrial Knowledge Graphs
Soft Skills
MentoringProblem SolvingCollaboration
Tools & Technologies
Cognite Data FusionCognite ToolkitREST APIVersion ControlCI/CD
Certifications & Qualifications
Cognite Academy Training
Industry Keywords
Oil & GasUpstreamDownstreamOperational DataEnterprise DataEngineering InformationHistoriansMaintenance SystemsLaboratory SystemsWell-Data Services
Tech Stack
Tools & technologiesCloudPythonSQL
About the role
Key responsibilities & impact- Design industrial data solutions for upstream and downstream Oil & Gas operations
- Define integration, modelling and contextualization of operational, enterprise and engineering information in Cognite Data Fusion
- Own solution architecture decisions and establish reusable implementation patterns
- Translate operational use cases into data requirements, integration designs and application-consumption patterns
- Define CDF’s role within historian, enterprise application, engineering information and cloud architectures
- Select extractors, APIs and processing patterns based on latency, throughput, connectivity and source-system load
- Define historical loading, incremental extraction, reconciliation and recovery approaches
- Establish requirements for service identities, access capabilities, environment separation, monitoring and operational support
- Design CDF models using spaces, containers, views and instances
- Reuse and extend Cognite’s Core Data Model and introduce custom domain concepts where required
- Define identifiers, source crosswalks, conflict-resolution rules, schema versioning and migration requirements
- Model equipment, assets, facilities, wells, process units, maintenance records, documents, diagrams and production data according to upstream/downstream semantics
- Design contextualization relationships and define matching rules, confidence thresholds and exception handling
- Validate contextualized information against intended engineering workflows
- Define consumer data contracts covering entities, relationships, fields, freshness, permissions and query performance
- Validate designs against Cognite applications, custom applications and analytical or AI workflows
- Develop prototypes and reference implementations using Python, SQL, Cognite SDKs and APIs
- Establish deployment and environment-promotion practices using version control, automated validation and Cognite Toolkit
- Review architecture changes, migration plans, integration code and performance bottlenecks
- Resolve cross-system design conflicts and mentor data engineering leads
Requirements
What you’ll need- Relevant engineering, computer science or information systems degree, or equivalent technical experience
- Experience level: 15+
- Demonstrated personal architectural contribution to a production Cognite Data Fusion implementation
- Strong knowledge of CDF data modelling, transformations, contextualization and access controls
- Substantial industrial data integration experience spanning operational, enterprise and engineering sources
- Strong Python and SQL skills
- Practical Cognite SDK and REST API experience
- Experience defining identity strategies, model evolution, deployment patterns and production support requirements
- Working knowledge of cloud architecture, identity providers, network boundaries and CI/CD
- Strong Oil & Gas implementation experience in at least one upstream or downstream domain, with ability to adapt relevant concepts to the other
- Cognite implementation experience across multiple assets or sites
- Experience spanning both upstream and downstream
- Familiarity with historians, maintenance systems, laboratory systems, engineering repositories or well-data services
- Experience with diagram contextualization, 3D associations and industrial knowledge graphs
- Experience enabling Cognite applications or AI workflows using contextualized data
- Relevant Cognite Academy training or certifications
Benefits
Comp & perks- Opportunity to solve high-impact industrial data and analytics challenges across upstream and downstream Oil & Gas
- Hands-on leadership role with scope to establish reusable practices and guide multidisciplinary teams
- Collaborative environment spanning domain engineering, data, technology, product and global EY teams
- Access to EY’s global network, technology ecosystem and learning opportunities
- Opportunity to contribute to a better working world