- Location
- Zürich, Switzerland
- Workplace
- Hybrid
- Type
- Full-time
- Department
- Data Engineering
- Seniority
- Senior
- Experience
- 4+ years
- Source
- Greenhouse
Description
Who/What is Artefact?
Artefact is a next-generation strategy and data consulting firm dedicated to transforming organizations through data and AI. We combine the rigor of top-tier strategy consulting with deep expertise in data, digital, and analytics to help clients achieve tangible
business impact.
With 1,800+ consultants, data scientists, and engineers across 23 countries, we work with global leaders such as Samsung, L’Oréal, Orange, and Sanofi. Our Zurich office is at the heart of Artefact’s growth, advising clients on their most pressing strategic challenges — from AI strategy and governance to digital transformation roadmaps and new business model design.
The role:
We are looking for a Senior Data & AI Architect who combines business strategy and technology across Data and GenAI. You will design the operating model and the organization of the Data & GenAI CoE, define the target architecture, and steer data products from demand through to rollout.
Key responsibilities:
Operating model and organization
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Design the Data & AI operating model (centralized, federated, hub-and-spoke) following Data Mesh principles: roles, responsibilities, domain ownership and governance mechanisms.
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Define the organization of the Data & GenAI CoE: scope, service catalogue, skills, sizing and engagement model with business domains.
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Design end-to-end processes for demand management, use case prioritization, funding and value tracking.
Architecture and technology choices
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Define the target data platform architecture on cloud (Azure, AWS, GCP) and Databricks, including GenAI components (RAG, agents, vector stores, LLMOps).
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Run make-or-buy analyses and vendor selections: scouting, evaluation criteria, business case, TCO and final recommendation.
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Check that architecture, security and data governance choices are consistent with enterprise standards and with the operating model.
Data products: from demand to rollout
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Gather and formalize functional requirements with the business, translating them into data products with owners, consumers, SLAs and quality metrics.
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Design data products from both a functional angle (use cases, KPIs, impacted processes) and a technical one (data model, pipelines, interfaces, serving layer).
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Act as design authority during implementation: review system integrator solutions and oversee quality, progress and risks of the rollout.
Requirements:
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At least 4 years of professional experience in IT.
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At least 2 years on projects focused on AI/GenAI, Data Mesh and functional requirements gathering.
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Consulting experience, ideally in strategy consulting, combined with experience at a system integrator or delivery firm.
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Hands-on experience designing operating models, Data/AI organizations or CoEs.
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Experience with make-or-buy analyses, vendor selection or target architecture definition.
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Excellent written and spoken English.
Technical and functional skills:
You will not be expected to write code, but you need to know the technologies well enough to assess them, challenge vendors and spot a flawed setup.
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Data Mesh and governance: domain ownership, data products, federated governance, data contracts, catalogues and lineage (e.g. Unity Catalog, OpenMetadata, Collibra).
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Cloud: data and AI PaaS services on at least one of Azure, AWS and GCP; security, networking and FinOps principles.
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Databricks: Lakehouse, Delta Lake, Unity Catalog, Workflows; ability to assess design and cost.
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GenAI: RAG and agentic architectures, LLMOps, model evaluation, platforms such as Azure AI Foundry, Vertex AI and Bedrock.
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Operating model: Data/AI organization, CoE, roles (data owner, data steward, product owner), demand and portfolio processes.
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Requirements and delivery: requirements gathering, user stories, process modelling, agile methods, programme governance.
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Business: business cases, TCO, value tracking, and the ability to translate technical choices into economic impact.
Nice to have:
-
German not strictly required.
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Experience with clients in pharma sector.
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Cloud or Databricks certifications (e.g. Azure Solutions Architect, Databricks Data Engineer or Solutions Architect).
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Experience in tech due diligence or post-merger transformation projects.
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Prior technical background as an engineer or developer.
What we offer:
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A role bridging strategy and technology, with direct impact on client decisions.
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International projects on Data Mesh, data platforms and GenAI.
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Close collaboration with the Project Lead and a growth path towards programme leadership roles.
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Location and working model: (Hybrid) Zurich or Lausanne.
- Highly competitive compensation package
This position is based in Zürich.
Don’t worry if you don’t meet all the criteria! We value motivation, pragmatic problem-solving, and potential above all else. We’d love to hear from you and learn more about your passion for driving the AI revolution.
Skills
AWSAzureGCPDatabricks