Data Architect

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world. 

Job Description

We are seeking a highly experienced Senior Data Architect to lead the design, modernization, and governance of enterprise data platforms. This role defines data architecture standards, shaping data platform strategy, and enabling high-quality, secure, and scalable data assets for analytics, AI/ML, GenAI, and mission-critical business operations.
You will collaborate closely with business, data engineering, analytics, cloud, security, and governance teams to build resilient data ecosystems aligned with organizational goals and industry best practices.

Job Description - Grade Specific

Key Responsibilities

· Define and maintain the enterprise Azure data architecture, covering ingestion, storage, processing, modeling, and consumption layers.

· Develop cloud-native data lakehouse architecture using ADLS Gen2, Delta Lake, Azure Databricks, and/or Microsoft Fabric.

· Set architecture standards for Azure services: Data ingestion: ADF, Event Hub, IoT Hub Data processing: Databricks, Fabric Data Engineering, Synapse Spark Data serving: Azure SQL, Synapse SQL Pools, Cosmos DB, Fabric Lakehouse/Warehouse Observability: Log Analytics, Monitor, Application Insights

· Drive modernization from legacy on-prem to Azure-based platforms.

· Lead conceptual, logical, and physical data modeling for Azure:

· Establish modeling standards aligned with Fabric, Synapse, and Databricks.

· Architect solutions leveraging:

· Define integration patterns for batch, micro-batch, real-time, and event-driven workloads.

· Implement data governance using Microsoft Purview:

· Ensure secure data architecture aligned with Azure capabilities:

· Architect datasets and pipelines for ML and GenAI workloads using:

o Azure Machine Learning (Azure ML)

o Databricks ML

o Azure AI Search for RAG/semantic search

o Vector stores (Fabric, Cognitive Search vectors, Databricks Vector DB)

· Ensure dataset curation, data quality, and governance in AI pipelines.

· Define data patterns for LLM applications (embeddings, grounding data, prompt history, auditability).

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.
Make it real | www.capgemini.com