岗位大厅/Engineering/Senior Data & AI Architect

Artefact · 9天前 · 来源 公开招聘平台

Senior Data & AI Architect

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<p><strong>Artefact是做什么的?</strong><br>Artefact是一家致力于通过数据和AI改造组织的下一代战略和数据咨询公司。我们结合顶级战略咨询的严谨性和在数据、数字和数据分析方面的深厚专业知识,帮助客户实现可衡量的商业影响。<br>拥有1,800多名顾问、数据科学家和工程师遍布23个国家,我们与三星、欧莱雅……

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必备技能

AIAWSAgentic AIAgileAnalyticsAzureCloudCollibraData GovernanceData Mesh

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职位描述 · 原文

<p><strong>Who/What is Artefact?</strong><br>Artefact is a next-generation strategy and data consulting firm dedicated to transforming&nbsp;organizations through data and AI. We combine the rigor of top-tier strategy consulting&nbsp;with deep expertise in data, digital, and analytics to help clients achieve tangible<br>business impact.<br>With 1,800+ consultants, data scientists, and engineers across 23 countries, we work&nbsp;with global leaders such as Samsung, L’Oréal, Orange, and Sanofi. Our Zurich office is&nbsp;at the heart of Artefact’s growth, advising clients on their most pressing strategic&nbsp;challenges — from AI strategy and governance to digital transformation roadmaps and&nbsp;new business model design.</p>
<p>&nbsp;</p>
<div><strong>The role:</strong></div>
<div>&nbsp;</div>
<div>We are looking for a Senior Data &amp; AI Architect who combines business strategy and technology across Data and GenAI. You will design the operating model and the organization of the Data &amp; GenAI CoE, define the target architecture, and steer data products from demand through to rollout.</div>
<div>&nbsp;</div>
<div><strong>Key responsibilities:</strong></div>
<div>&nbsp;</div>
<div>Operating model and organization</div>
<ul>
<li>
<div>Design the Data &amp; AI operating model (centralized, federated, hub-and-spoke) following Data Mesh principles: roles, responsibilities, domain ownership and governance mechanisms.</div>
</li>
<li>
<div>Define the organization of the Data &amp; GenAI CoE: scope, service catalogue, skills, sizing and engagement model with business domains.</div>
</li>
<li>
<div>Design end-to-end processes for demand management, use case prioritization, funding and value tracking.</div>
</li>
</ul>
<div>Architecture and technology choices</div>
<ul>
<li>
<div>Define the target data platform architecture on cloud (Azure, AWS, GCP) and Databricks, including GenAI components (RAG, agents, vector stores, LLMOps).</div>
</li>
<li>
<div>Run make-or-buy analyses and vendor selections: scouting, evaluation criteria, business case, TCO and final recommendation.</div>
</li>
<li>
<div>Check that architecture, security and data governance choices are consistent with enterprise standards and with the operating model.</div>
</li>
</ul>
<div>Data products: from demand to rollout</div>
<ul>
<li>
<div>Gather and formalize functional requirements with the business, translating them into data products with owners, consumers, SLAs and quality metrics.</div>
</li>
<li>
<div>Design data products from both a functional angle (use cases, KPIs, impacted processes) and a technical one (data model, pipelines, interfaces, serving layer).</div>
</li>
<li>
<div>Act as design authority during implementation: review system integrator solutions and oversee quality, progress and risks of the rollout.</div>
</li>
</ul>
<div><strong>Requirements:</strong></div>
<ul>
<li>
<div>At least 4 years of professional experience in IT.</div>
</li>
<li>
<div>At least 2 years on projects focused on AI/GenAI, Data Mesh and functional requirements gathering.</div>
</li>
<li>
<div>Consulting experience, ideally in strategy consulting, combined with experience at a system integrator or delivery firm.</div>
</li>
<li>
<div>Hands-on experience designing operating models, Data/AI organizations or CoEs.</div>
</li>
<li>
<div>Experience with make-or-buy analyses, vendor selection or target architecture definition.</div>
</li>
<li>
<div>Excellent written and spoken English.</div>
</li>
</ul>
<div>Technical and functional skills:</div>
<div>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.</div>
<ul>
<li>
<div>Data Mesh and governance: domain ownership, data products, federated governance, data contracts, catalogues and lineage (e.g. Unity Catalog, OpenMetadata, Collibra).</div>
</li>
<li>
<div>Cloud: data and AI PaaS services on at least one of Azure, AWS and GCP; security, networking and FinOps principles.</div>
</li>
<li>
<div>Databricks: Lakehouse, Delta Lake, Unity Catalog, Workflows; ability to assess design and cost.</div>
</li>
<li>
<div>GenAI: RAG and agentic architectures, LLMOps, model evaluation, platforms such as Azure AI Foundry, Vertex AI and Bedrock.</div>
</li>
<li>
<div>Operating model: Data/AI organization, CoE, roles (data owner, data steward, product owner), demand and portfolio processes.</div>
</li>
<li>
<div>Requirements and delivery: requirements gathering, user stories, process modelling, agile methods, programme governance.</div>
</li>
<li>
<div>Business: business cases, TCO, value tracking, and the ability to translate technical choices into economic impact.</div>
</li>
</ul>
<div>Nice to have:</div>
<ul>
<li>
<div>German not strictly required.</div>
</li>
<li>
<div>Experience with clients in pharma sector.</div>
</li>
<li>
<div>Cloud or Databricks certifications (e.g. Azure Solutions Architect, Databricks Data Engineer or Solutions Architect).</div>
</li>
<li>
<div>Experience in tech due diligence or post-merger transformation projects.</div>
</li>
<li>
<div>Prior technical background as an engineer or developer.</div>
</li>
</ul>
<div><strong>What we offer:</strong></div>
<ul>
<li>
<div>A role bridging strategy and technology, with direct impact on client decisions.</div>
</li>
<li>
<div>International projects on Data Mesh, data platforms and GenAI.</div>
</li>
<li>
<div>Close collaboration with the Project Lead and a growth path towards programme leadership roles.</div>
</li>
<li>
<div>Location and working model: (Hybrid) Zurich or Lausanne.</div>
</li>
<li>Highly competitive compensation package</li>
</ul>
<p>&nbsp;</p>
<p>This position is based in <strong>Zürich</strong>.</p>
<p><em>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.</em></p>
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可以投——没有红灯,黄灯问题放进面试清单问清即可。
deep expertise → 「用过能干活」级——符合 60% 就值得投
nice to have → 加分项,不是门槛
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公司 · Company

Artefact

—

Zürich来源:公开招聘平台

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