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RQ00239 - Senior Data Architect

Flexstaf IT109 open roles

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Your applicationOpen nowRQ00239 - Senior Data ArchitectFlexstaf IT

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Share of postings closed within
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  2. 4.6%3 days
  3. 13.4%7 days
  4. 21.6%14 days
  5. 36.2%30 days
  6. 59.0%60 days
This job: first seen 7 minutes ago

The posting

MSP Notes

Shortlist Date: Nov 9, 2026 10:00am

Must Haves:

  • Significant experience designing enterprise data architectures and conceptual, logical, and physical data models for AI/ML, Generative AI, analytics, and cloud workloads, including the data requirements for model training, inference, RAG, feature engineering, and AI/ML pipelines.
  • Deep technical expertise in modern cloud data platforms, data engineering, integration, APIs, metadata, lineage, and data quality, with strong knowledge of the Azure data and AI ecosystem, Azure Machine Learning, and Microsoft Foundry/Azure AI Foundry, and architectural patterns supporting scalable AI/ML solutions.
  • Strong understanding of data governance, data ownership, lineage, data quality, security, privacy, and information lifecycle management, with the ability to design governed, traceable, and fit-for-purpose data architectures that support the AI/ML and model lifecycle.

Location: Hybrid – 3 days a week onsite

Public Sector Experience: preferred but not required

# of submissions/supplier: 1

Job Title

Senior Data Architect/Modeller

Description

The Senior Data Architect/Modeller will design and evolve enterprise data architecture and data models to enable scalable analytics, AI, and data products. The role will help establish the future-state data architecture, identify critical data assets, and define standards and integration patterns that enable data to be governed, reusable, accessible, and AI-ready.

Key Responsibilities

  • Design and maintain enterprise data architecture and conceptual, logical, and physical data models supporting AI, analytics, and operational use cases.
  • Define scalable architecture patterns for the integration, storage, transformation, sharing, and consumption of enterprise data.
  • Design reusable data products and common data models that can support multiple business and AI use cases.
  • Contribute to the organization's future-state data architecture, including transition from existing platforms and architectures.
  • Identify and define critical data assets and domains required to support enterprise priorities.
  • Establish and promote enterprise data architecture, modelling, interoperability, and integration standards.
  • Partner with Data Governance teams to embed data ownership, quality, metadata, lineage, classification, and lifecycle requirements into architecture and data products.
  • Assess data requirements and architecture implications for AI, Generative AI, machine learning, advanced analytics, and reporting initiatives.
  • Work with business, Data & AI, architecture, engineering, and technology teams to translate business requirements into scalable data solutions.
  • Identify architecture gaps, duplication, data silos, and opportunities to improve data reuse and interoperability across the enterprise.

Qualifications & Experience

  • Degree in Computer Science, Information Systems, Data Management, Engineering, or a related discipline, or equivalent experience.
  • Significant experience in enterprise data architecture, data modelling, data engineering, or related disciplines.
  • Demonstrated experience developing conceptual, logical, and physical data models and enterprise data architectures.
  • Experience designing modern data architectures supporting cloud, analytics, AI/ML, and enterprise integration.
  • Strong knowledge of data modelling, data integration, APIs, data platforms, metadata, master/reference data, and data quality concepts.
  • Understanding of data governance, data ownership, lineage, security, privacy, and information lifecycle management.
  • Knowledge of modern architecture approaches such as data lakehouse, data products, domain-oriented architecture, and cloud-based data platforms.
  • Ability to translate complex business and technical requirements into practical architecture standards, models, and patterns.
  • Strong stakeholder management, communication, documentation, and problem-solving skills.
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