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Sopra Steria

IT consulting, digital services, and transformation

Enterprise Architect - Data & AI

Data ManagementConfirmed live in the last 24 hours
Full-timeBrussels, BelgiumNo salary listedHybrid

About the Job

Requirements

  • Extensive experience in data architecture, solution architecture, enterprise architecture, or comparable technical leadership roles, with strong exposure to Data & AI.
  • Proven experience designing or governing large-scale data platforms, such as data lakes, data warehouses, lakehouse architectures, or equivalent modern data ecosystems.
  • Strong understanding of data modelling and architecture approaches, such as dimensional modelling, Data Vault, domain-driven data design, data mesh, or data fabric.
  • Good understanding of the AI/ML lifecycle, including model development, deployment, monitoring, and MLOps practices.
  • Familiarity with Generative AI and LLM architectures, including Retrieval-Augmented Generation (RAG), vector databases, model orchestration, and LLMOps.
  • Experience with one or more major cloud Data & AI ecosystems, such as Microsoft Azure, AWS, or Google Cloud, and/or platforms such as Databricks or Snowflake.
  • Strong understanding of data governance, metadata management, data cataloguing, and data quality.
  • Familiarity with enterprise architecture frameworks and modelling approaches such as TOGAF, Zachman, or ArchiMate.
  • Understanding of security, privacy, and regulatory considerations for Data & AI, including GDPR and the EU AI Act.
  • Strong communication and stakeholder management skills, with the ability to engage effectively with technical teams and senior business stakeholders.

Responsibilities

  • Define and evolve the enterprise Data & AI architecture vision, including target-state architectures, reference architectures, architecture principles, and technology roadmaps.
  • Establish and promote standards for data modelling, governance, master data management, data quality, metadata management, and data lifecycle management.
  • Design and validate architectures for modern data platforms, including data lakes, data warehouses, lakehouses, and streaming solutions across cloud, hybrid, and where relevant on-premises environments.
  • Define architecture patterns for AI and ML capabilities, including MLOps, model lifecycle management, model monitoring, and integration with enterprise data platforms.
  • Define scalable and secure architecture patterns for Generative AI and LLM-based solutions, including RAG, enterprise data integration, model access, orchestration, and governance.
  • Partner with business and technology stakeholders to translate strategic objectives and use cases into Data & AI capabilities and architecture roadmaps.
  • Guide project and engineering teams on architecture decisions, facilitate architecture reviews, and promote alignment with enterprise standards and design principles.
  • Assess technologies, platforms, and vendors across cloud, data, analytics, AI, and machine learning, balancing business value, technical fit, security, cost, and long-term sustainability.
  • Ensure that privacy, security, responsible AI, and applicable regulatory requirements are considered throughout architecture and design decisions.
  • Help define architecture guardrails around model risk, transparency, explainability, monitoring, and responsible use of AI.
  • Act as a trusted architecture advisor to data engineering, analytics, AI, and data science teams, sharing best practices and supporting complex architecture decisions.
  • Work closely with fellow enterprise architects across applications, infrastructure, security, integration, and cloud to ensure architectural coherence.
  • Stay informed about developments in data platforms, AI/ML, and Generative AI and assess where emerging technologies can create meaningful value for the organisation.

Desired Qualifications

  • Relevant certifications are considered an advantage, including TOGAF, ArchiMate, Databricks certifications, Microsoft Azure Data or AI certifications, AWS Data or Machine Learning certifications, or Google Cloud Data or Machine Learning certifications.

About the Company

Sopra Steria

IT consulting, digital services, and transformation

Sopra Steria provides consulting, digital services and solutions to help large organizations transform their business through technology. Its offerings cover strategy, systems integration, cloud, cyber security, software development, and managed services, designed to be delivered end to end—from assessing needs and designing a plan to implementing and operating IT systems. The company combines deep knowledge of many industries with a collaborative approach to tailor projects to each client and to deliver measurable, sustainable improvements in performance. Differentiators include its European scale (about 51,000 employees across roughly 30 countries), broad scope—from strategy to operation—and emphasis on practical outcomes that help clients stay competitive. The group’s goal is to put digital to work for its clients in a way that creates a positive, more productive future for all stakeholders.

Company size
10,001+
Company stage
IPO
Headquarters
Paris, France
Founded
1968

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