AI Data Architect

Description

The company is the company Digital Services, a global digital solutions and transformation business. Its people work on projects that range from urban infrastructure and natural resource conservation to saving lives.

The role is for an AI Data Architect who designs the semantic, knowledge and governance layers so that AI agents can work on trusted, well-structured and governed data.

The team is a global group of engineers who build data-driven solutions for organizations in many industries.

The company operates across many industries and regions and values diverse perspectives. It applies merit-based systems and aims for an inclusive culture.

You do not need to match every requirement. Life experience, character and perspective count as much as the listed skills.

The company is an equal opportunity employer and welcomes applicants regardless of protected characteristics. Reasonable accommodations are available during recruitment on request.

Responsibilities

• Build the metrics layer, ontology framework, search indexes and business glossary.
• Assess data readiness on scope, freshness, semantic clarity, quality, governance, usability and operational effectiveness.
• Gather business rules from subject matter experts and turn them into models that can be reused, governed and scaled.
• Set up entitlement frameworks, data lineage standards and requirements for agent identity.

Requirements

• Hands-on work with lakehouse and cloud data platforms, preferably Databricks, including Delta Lake, Unity Catalog, PySpark or comparable tools.
• Solid grasp of semantic and metrics layers, dimensional modeling and domain-driven data design.
• Practical experience with ontologies and knowledge graphs such as RDF/OWL, Neo4j or other property graph tools.
• Experience with vector databases, semantic search, embeddings and Retrieval-Augmented Generation (RAG) architectures.
• Thorough knowledge of data governance, covering lineage, access management, business glossaries and master data management.
• Experience implementing event-driven architectures and business rules with tools like Kafka, Amazon MSK, alerting platforms and rules engines.
• Skill in data quality management, reconciliation and data readiness assessment.
• 12+ years in data architecture, data engineering or analytics architecture.
• Proven delivery of at least one enterprise-scale semantic layer, knowledge graph or governed data product.
• Experience running requirements workshops with business SMEs and presenting architecture recommendations to senior leaders and stakeholders.
• Optional: experience in automotive, manufacturing or supply chain environments.
• Optional: exposure to GenAI grounding, text-to-SQL solutions and natural language analytics platforms.
• Optional: professional certifications in Databricks, cloud architecture or data architecture.

Conditions

Flexible working arrangements are offered, depending on role and location.

Benefits

• Industry-leading benefits, support and services for holistic health and wellbeing.
• A culture of ownership and autonomy, with colleagues you enjoy learning from.