Enterprise Architect (Data & AI) is a AI Solutions Architect role (full-time). with Sopra Steria. in BRUXELLES - BRUSSEL, BE. Imported listing (source: be.engineering.jobs). Apply on the employer's site (be.engineering.jobs).
Imported listing (source: be.engineering.jobs) · Apply on be.engineering.jobs
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Imported job description
Sourced from be.engineering.jobs
Sopra Steria is seeking an Enterprise Architect specializing in Data & AI to define and evolve the enterprise-wide data and AI architecture vision. You will work at the intersection of business strategy, enterprise architecture, data engineering, and AI/ML, translating strategic objectives into architecture principles, target-state architectures, technology roadmaps, and practical guidance for delivery teams. The role involves designing scalable, secure, and well-governed platforms and capabilities for data, analytics, AI, and Generative AI.
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 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.
Sopra Steria is a major European technology services group providing consulting, digital services, software development, and end-to-end solutions. It helps large organizations pursue digital transformation across sectors including aerospace, defense and security, financial services, and energy.
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.
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 concepts such as 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 areas such as GDPR and the EU AI Act.
Strong communication and stakeholder management skills, with the ability to engage effectively with both technical teams and senior business stakeholders.
Nice to Have
Relevant certifications such as TOGAF, ArchiMate, Databricks certifications, Microsoft Azure Data or AI certifications, AWS Data or Machine Learning certifications, Google Cloud Data or Machine Learning certifications.
Ability to translate business strategy into clear Data & AI architecture choices and roadmaps.
Ability to move comfortably between strategic architecture discussions and more detailed technical conversations with engineering and AI teams.
Ability to build alignment across business, architecture, security, data, and technology stakeholders.
Pragmatic approach to architecture, balancing long-term direction with delivery realities.
Ability to provide direction in a rapidly evolving technology landscape and distinguish meaningful innovation from short-lived trends.
Ability to communicate complex Data & AI concepts clearly to both technical and non-technical audiences.
Benefits
Health insurancepaid time offcompany carLearning & developmentphone and laptop
