Enterprise Architect (Data & AI)
Sopra Steria is hiring an Enterprise Architect (Data & AI) in Brussels, Belgium. Level rates it ; you can apply on Sopra Steria.
Level's read on this job
- Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting mentions Databricks, RAG and MLOps among its tools and skills.
- Sopra Steria has 2,000+ other open roles on Level.
AI in this role
Sopra Steria offers tailored, end-to-end corporate technology and software solutions to help clients make bold choices and deliver results. Successfully so! With more than 51.000 colleagues in 30 countries, we rank as Europe’s leading digital solutions provider. Some of the most successful companies in Europe rely on our technology due to our commitment to innovation, collaboration, and value in business development.
The world is how we shape it. Let’s shape it together.
We are looking for an Enterprise Architect specializing in Data & AI to join our architecture team and help shape our enterprise-wide data and AI landscape.
In this role, you will define and evolve the architecture vision for data, analytics, AI, and Generative AI, ensuring that platforms and capabilities are scalable, secure, well-governed, and aligned with business priorities.
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.
Key Responsibilities
- Vision & Roadmap: Define and evolve the enterprise Data & AI architecture vision, including target-state architectures, reference architectures, architecture principles, and technology roadmaps.
- Data Architecture & Standards: Establish and promote standards for data modelling, governance, master data management, data quality, metadata management, and data lifecycle management.
- Data Platforms: 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.
- AI & ML Architecture: Define architecture patterns for AI and ML capabilities, including MLOps, model lifecycle management, model monitoring, and integration with enterprise data platforms.
- Generative AI: Define scalable and secure architecture patterns for Generative AI and LLM-based solutions, including RAG, enterprise data integration, model access, orchestration, and governance.
- Business Alignment: Partner with business and technology stakeholders to translate strategic objectives and use cases into Data & AI capabilities and architecture roadmaps.
- Architecture Governance: Guide project and engineering teams on architecture decisions, facilitate architecture reviews, and promote alignment with enterprise standards and design principles.
- Technology Evaluation: Assess technologies, platforms, and vendors across cloud, data, analytics, AI, and machine learning, balancing business value, technical fit, security, cost, and long-term sustainability.
- Data & AI Governance: Ensure that privacy, security, responsible AI, and applicable regulatory requirements are considered throughout architecture and design decisions.
- Responsible AI: Help define architecture guardrails around model risk, transparency, explainability, monitoring, and responsible use of AI.
- Technical Leadership: Act as a trusted architecture advisor to data engineering, analytics, AI, and data science teams, sharing best practices and supporting complex architecture decisions.
- Enterprise Collaboration: Work closely with fellow enterprise architects across applications, infrastructure, security, integration, and cloud to ensure architectural coherence.
- Innovation & Technology Watch: Stay informed about developments in data platforms, AI/ML, and Generative AI and assess where emerging technologies can create meaningful value for the organisation.
Your Experience & Expertise
- 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.
Certifications
Relevant certifications are considered an advantage, for example:
- TOGAF
- ArchiMate
- Databricks certifications
- Microsoft Azure Data or AI certifications
- AWS Data or Machine Learning certifications
- Google Cloud Data or Machine Learning certifications
Equivalent expertise demonstrated through professional experience is equally valued.
What Will Help You Succeed
- You can translate business strategy into clear Data & AI architecture choices and roadmaps.
- You are able to move comfortably between strategic architecture discussions and more detailed technical conversations with engineering and AI teams.
- You build alignment across business, architecture, security, data, and technology stakeholders.
- You take a pragmatic approach to architecture, balancing long-term direction with delivery realities.
- You can provide direction in a rapidly evolving technology landscape and distinguish meaningful innovation from short-lived trends.
- You communicate complex Data & AI concepts clearly to both technical and non-technical audiences.
Our employees are known for making bold choices and delivering results. Work among high-level professionals at the forefront of corporate software solutions and innovation at Europe’s Leading Digital Service Provider.
We offer a generous employee benefits package that includes:
- A competitive salary and an indefinite contract
- A company car or mobility budget
- Comprehensive insurance coverage (hospitalisation, outpatient care and group insurance)
- 32 days paid time off (20 days + 12 bonus days)
- Laptop, phone and mobile subscription
- Continuous learning opportunities through the Sopra Steria Academy to support your career development
People are the cornerstone of our success. That’s why we aspire to be bold together. Our goal is to provide healthy team environments to build high-functioning teams that inspire and help each other to deliver excellence for our customers.
Excited about this job opportunity? Ready to shape the world with us? Great! We are looking forward to your application!
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Sopra Steria is an equal opportunity employer. All qualified applicants will be considered for employment without regard to age, ancestry, nationality, color, family or medical leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, gender (including pregnancy), sexual orientation or any other characteristic protected by applicable local laws, regulations and ordinances. We foster a work environment that is inclusive and respectful of all differences.
How we rate this
Enterprise Architect (Data & AI) at Sopra Steria rates 77 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- How do you think about the risk of an AI system in this kind of role failing silently?
- What's a project where you used Databricks hands-on?
- Describe a typical day in a role like this one: which parts run through AI directly?
Adapt your resume
- List these exact terms on your resume: RAG, ML Ops, AI Safety, and Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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