At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Cognite Solution Architect – Senior Manager

Experience Level - 15+

Job Description

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. We’re counting on your unique voice and perspective to help EY become even better. Join us and help build a better working world.

We are seeking a hands-on Cognite Solution Architect to design industrial data solutions for upstream and downstream Oil & Gas operations. You will define how operational, enterprise and engineering information is integrated, modelled and contextualized in Cognite Data Fusion (CDF), and how applications and analytical solutions consume that information. You will own solution architecture decisions, establish reusable implementation patterns and resolve complex technical issues across source systems, data models, access controls and consuming applications.

Role Details

Key responsibilities include:

Architecture and integration

Translate operational use cases into data requirements, integration designs and application-consumption patterns.
Define how CDF fits within historian, enterprise application, engineering information and cloud architectures.
Select source-appropriate extractors, APIs and processing patterns, considering latency, throughput, connectivity and source-system load.
Define historical loading, incremental extraction, reconciliation and recovery approaches, including late records, corrections and supported deletions.
Establish requirements for service identities, access capabilities, environment separation, monitoring and operational support.

Industrial information modelling

Design CDF models using spaces, containers, views and instances; select direct relations or edges according to relationship semantics and query requirements.
Reuse and extend Cognite’s Core Data Model where suitable, introducing custom domain concepts where required.
Define stable identifiers, source crosswalks and conflict-resolution rules, including repeated tag names across sites and systems.
Represent physical equipment, functional locations and installation history separately where required.
Establish schema versioning, migration and consumer-compatibility requirements while preserving lineage, timestamps, units, quality indicators and relationship provenance.

Contextualization and Oil & Gas semantics

Design relationships connecting equipment and assets with time series, maintenance records, documents and engineering diagrams.
Define matching rules, confidence thresholds, exception handling and domain review for ambiguous associations; assess coverage and match accuracy separately.
For upstream applications, model fields, wells, wellbores, production facilities, equipment, well tests and interventions, preserving distinctions between measured, calculated and allocated production.
For downstream applications, model sites, process units, functional locations, equipment, laboratory results and maintenance activities, accounting for replacement, revisions and measurement timing.
Validate that contextualized information supports the intended engineering workflow.
Application enablement and technical assurance
Define consumer data contracts covering entities, relationships, fields, freshness, permissions and query-performance expectations.
Validate designs against representative Cognite applications, custom applications, and analytical or AI workflows.
Develop critical 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.

Must Have Qualifications & Experience

A relevant engineering, computer science or information systems degree, or equivalent technical experience.
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 representative operational, enterprise and engineering sources.
Strong Python and SQL skills with 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.

Good to Have

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.

What We Offer

Opportunity to solve high-impact industrial data and analytics challenges across upstream and downstream Oil & Gas.
A hands-on leadership role with scope to establish reusable practices and guide multidisciplinary teams.
A collaborative environment spanning domain engineering, data, technology, product and global EY teams.
Access to EY’s global network, technology ecosystem and learning opportunities while contributing to a better working world.

What We Look For

A hands-on architect who can defend consequential production Cognite decisions involving identity resolution, data-model design, access boundaries, recovery, schema migration and application compatibility, and demonstrate which patterns can be reused across sites and which require adaptation.

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