Publié il y a 10 jours
Senior Data Architect / Modeler - Contract
@ Compugen Inc
Toronto, Ontario
SIGNAUX
Résumé des exigences :
- To innovate industries, transform businesses, connect communities, and drive meaningful change, we must think bigger, reach broader, and act bolder.
- Through knowledge, curiosity, and collaboration, Compugen helps organizations delivering experience by design.
- The ideal candidate will bring deep technical expertise in enterprise data architecture, modern cloud data platforms, Microsoft Azure AI technologies, and data governance, with the ability…
- Identify, assess, and define critical enterprise data assets, data domains, and information requirements aligned with organizational priorities.
- Design data architectures supporting AI/ML pipelines, model training, inference, feature engineering, and RAG/grounding data requirements.
- Assess data architecture requirements for Generative AI, predictive analytics, machine learning, business intelligence, and enterprise reporting initiatives.
Source et dates
Type de source non vérifié · apify-linkedin
- Date publiée par l’employeur
- 2026-11-03
- Première détection par notre source
- 2026-11-14
- Mise à jour du dossier source
- 2026-11-14
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Compugen Inc
| Champ | Valeur |
|---|---|
| Offres sur Jobsy | 5 |
Description
About Compugen Compugen is Canada's largest privately-owned Technology Ally. To innovate industries, transform businesses, connect communities, and drive meaningful change, we must think bigger, reach broader, and act bolder. Through knowledge, curiosity, and collaboration, Compugen helps organizations delivering experience by design. This is what it means to be human-centered and technology-enabled.
Dreaming, designing, and delivering isn't just a mantra for us — it's a way of life. We believe that technology is the conduit, but our people – they are the connection that truly makes the magic happen!
Our Culture We are a human-centered culture where we prioritize your well-being and are invested in helping you reach your fullest potential. We're not only focused on achieving our goals — we're dedicated to helping you achieve yours.
If you're relentlessly curious, driven to make a difference, and collaborative at the core, then you belong with us.
Position Overview: We are seeking an experienced Senior Data Architect/Modeller to design, develop, and evolve enterprise data architectures and data models that support Artificial Intelligence (AI), Generative AI, machine learning, advanced analytics, and enterprise data initiatives.
The successful candidate will be responsible for establishing scalable, secure, and governed data architectures, developing conceptual, logical, and physical data models, and defining reusable data products and integration patterns that enable enterprise-wide data accessibility and interoperability.
This role will focus on developing future-state data architecture, identifying critical enterprise data assets, and ensuring data platforms are optimized to support AI/ML workloads, including model training, inference, feature engineering, and Retrieval-Augmented Generation (RAG) solutions.
The ideal candidate will bring deep technical expertise in enterprise data architecture, modern cloud data platforms, Microsoft Azure AI technologies, and data governance, with the ability to translate complex business and technical requirements into scalable, AI-ready data solutions.
Key Responsibilities:
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#CompugenITR
Dreaming, designing, and delivering isn't just a mantra for us — it's a way of life. We believe that technology is the conduit, but our people – they are the connection that truly makes the magic happen!
Our Culture We are a human-centered culture where we prioritize your well-being and are invested in helping you reach your fullest potential. We're not only focused on achieving our goals — we're dedicated to helping you achieve yours.
If you're relentlessly curious, driven to make a difference, and collaborative at the core, then you belong with us.
Position Overview: We are seeking an experienced Senior Data Architect/Modeller to design, develop, and evolve enterprise data architectures and data models that support Artificial Intelligence (AI), Generative AI, machine learning, advanced analytics, and enterprise data initiatives.
The successful candidate will be responsible for establishing scalable, secure, and governed data architectures, developing conceptual, logical, and physical data models, and defining reusable data products and integration patterns that enable enterprise-wide data accessibility and interoperability.
This role will focus on developing future-state data architecture, identifying critical enterprise data assets, and ensuring data platforms are optimized to support AI/ML workloads, including model training, inference, feature engineering, and Retrieval-Augmented Generation (RAG) solutions.
The ideal candidate will bring deep technical expertise in enterprise data architecture, modern cloud data platforms, Microsoft Azure AI technologies, and data governance, with the ability to translate complex business and technical requirements into scalable, AI-ready data solutions.
Key Responsibilities:
- Design, develop, and maintain enterprise data architectures and conceptual, logical, and physical data models supporting AI/ML, Generative AI, analytics, and operational applications.
- Define scalable architecture patterns for enterprise data integration, storage, transformation, sharing, and consumption.
- Design reusable data products, common data models, and standardized data structures that support multiple business functions and AI initiatives.
- Develop and evolve future-state enterprise data architecture, including transition strategies from existing platforms and legacy environments.
- Identify, assess, and define critical enterprise data assets, data domains, and information requirements aligned with organizational priorities.
- Establish enterprise data architecture standards, data modelling methodologies, interoperability frameworks, and integration patterns.
- Design data architectures supporting AI/ML pipelines, model training, inference, feature engineering, and RAG/grounding data requirements.
- Provide architectural guidance for integrating enterprise data with Azure Machine Learning, Microsoft Azure AI Foundry, and related cloud-based AI services.
- Design modern cloud-based data architectures, including data lakehouse environments, domain-oriented data platforms, and enterprise analytics solutions.
- Define data integration approaches supporting enterprise applications, databases, APIs, cloud platforms, and data engineering pipelines.
- Collaborate with Data Governance teams to incorporate data ownership, quality, metadata, lineage, classification, security, privacy, and lifecycle management requirements into architecture designs.
- Ensure enterprise data architectures support traceability, reliability, scalability, and governance throughout the AI/ML and model lifecycle.
- Assess data architecture requirements for Generative AI, predictive analytics, machine learning, business intelligence, and enterprise reporting initiatives.
- Evaluate existing data environments to identify architectural gaps, data duplication, integration challenges, and opportunities to eliminate data silos.
- Define architectural approaches for master data, reference data, metadata management, and common enterprise data definitions.
- Collaborate with Data Engineers, Data Scientists, AI/ML Engineers, Solution Architects, and business stakeholders to translate requirements into scalable technical solutions.
- Provide technical guidance on data architecture, data modelling, integration standards, and reusable data services.
- Support architecture reviews, technical design assessments, and solution evaluations to ensure alignment with enterprise standards.
- Develop and maintain architecture documentation, data models, integration specifications, technical standards, and design artifacts.
- Identify opportunities to improve enterprise data accessibility, interoperability, reuse, performance, and long-term maintainability.
- Degree in Computer Science, Information Systems, Data Management, Engineering, or a related discipline, or equivalent professional experience.
- Extensive experience designing enterprise data architectures and conceptual, logical, and physical data models within complex enterprise environments.
- Demonstrated experience developing data architectures supporting AI/ML, Generative AI, advanced analytics, and cloud-based workloads.
- Strong understanding of data requirements for machine learning pipelines, model training, inference, feature engineering, and Retrieval-Augmented Generation (RAG) solutions.
- Deep technical expertise in modern cloud data platforms, enterprise data architecture, data engineering, and scalable integration patterns.
- Strong working knowledge of the Microsoft Azure data and AI ecosystem, including Azure Machine Learning and Microsoft Azure AI Foundry.
- Experience designing architecture patterns that support scalable, reliable, and production-ready AI/ML solutions.
- Strong knowledge of enterprise data modelling, data integration, APIs, data pipelines, and interoperability standards.
- Experience designing reusable data products, common data models, and domain-oriented data architectures.
- Knowledge of modern data architecture approaches, including data lakehouse, cloud-based data platforms, and enterprise analytics environments.
- Strong understanding of metadata management, data lineage, master data management, reference data, and data quality frameworks.
- Experience developing future-state data architectures, conducting architecture assessments, and defining transition strategies from legacy environments.
- Strong understanding of data governance, data ownership, classification, security, privacy, and information lifecycle management.
- Demonstrated ability to design governed, traceable, and fit-for-purpose data architectures that support the complete AI/ML model lifecycle.
- Experience identifying critical enterprise data assets, defining data domains, and establishing standardized data structures.
- Ability to assess data architecture implications for Generative AI, machine learning, predictive analytics, and enterprise reporting solutions.
- Experience identifying architectural gaps, eliminating data silos, and improving data accessibility and reuse across enterprise systems.
- Strong ability to translate complex business and technical requirements into practical architecture standards, data models, and integration solutions.
- Experience developing enterprise architecture documentation, technical specifications, data models, and integration standards.
- Excellent analytical, problem-solving, communication, and stakeholder management skills.
- Proven ability to collaborate with cross-functional business and technical teams, manage competing priorities, and deliver scalable enterprise data solutions.
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