Enterprise Data Architect

Enterprise Data Architect

Do you want to boost your career and collaborate with expert, talented colleagues to solve and deliver against our clients' most important challenges? We are growing and are looking for people to join our team. You'll be part of an entrepreneurial, high-growth environment of 300,000 employees. Our dynamic organization allows you to work across functional business pillars, contributing your ideas, experiences, diverse thinking, and a strong mindset. Are you ready?

About your role

Enterprise AI is forcing organizations to rethink their data estates. Data platforms designed mainly for reporting are often not enough for GenAI, semantic search, agentic workflows, and AI-enabled decision-making. Clients now need data that is trusted, governed, contextualized, and consumable by both people and intelligent systems.

We are looking for client-facing Enterprise Data Architects to join our growing Enterprise AI practice. You will help clients transform fragmented data estates into AI-ready foundations, advising on architecture decisions across cloud data platforms, lakehouse and warehouse patterns, data products, semantic layers, metadata, lineage, governance, knowledge graphs, and GenAI retrieval patterns.

This is a consulting role, not a purely internal architecture role. You will diagnose ambiguous client problems, shape options, make trade-offs explicit, and translate complex data architecture issues into clear decisions for both technical teams and executive stakeholders.

You will work in cross-functional teams alongside product owners, data scientists, ML and GenAI engineers, data engineers, business analysts, and client stakeholders.

Typical outputs may include target-state architectures, maturity assessments, platform option appraisals, data product designs, governance models, lineage maps, ontology and semantic models, integration patterns, GenAI data-readiness assessments, and implementation roadmaps.

We are hiring across several levels. At earlier levels, we expect strong architecture delivery experience and hands-on platform understanding. At senior levels, we expect the ability to shape enterprise data strategy, influence senior stakeholders, lead complex architecture decisions, and guide multi-disciplinary delivery teams.

We do not expect every candidate to be a specialist in every aspect of AI-ready data architecture. We are looking for architects with strong core data architecture experience and credible depth in some of the areas that matter for AI-enabled data estates, such as governance, semantic modeling, lakehouse architecture, data products, metadata management, knowledge graphs, RAG, or enterprise data strategy.