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Capgemini

Global consulting, technology services, outsourcing

Azure Data Solution Architect

Data EngineeringUpdated on Nov 15
Full-timeNo salary listed

About the Job

Requirements

  • At least 7 years of experience as a Data Architect, including designing, developing, and implementing Databricks solutions.
  • Expertise in Databricks, Apache Spark, and data platforms, with a strong understanding of data warehousing concepts and practices.
  • Experience with Microsoft Azure, including Azure Data Lake Storage, Databricks, and Azure Data Factory.
  • Relevant architecture certifications from Microsoft and Databricks.
  • Deep experience delivering data platforms and data architecture within complex public sector environments, including an understanding of government operating models, regulatory obligations, and trusted, mission-critical data.
  • Ability to design secure, scalable, and well-governed data foundations supporting analytics, AI, and GenAI while meeting data protection, sovereignty, transparency, and auditability requirements.
  • Ability to work with senior stakeholders to translate outcomes into pragmatic data and AI architectures, balancing innovation with risk management.
  • Ability to align multi-supplier delivery teams around shared standards, reuse platforms effectively, and build sustainable data capabilities.
  • Strong problem-solving and analytical skills.

Responsibilities

  • Design and build high-performance data platforms using Databricks and Apache Spark to extract, transform, and load data into Azure Data Lake Storage and other Azure services.
  • Design and oversee delivery of secure data warehouses and data lakehouses, implementing data models, data quality checks, and governance practices to ensure reliable and accurate data.
  • Design, build, and deploy AI/ML models; integrate machine learning into data pipelines and use Databricks ML and Azure ML to develop predictive models and drive business insights.
  • Design, monitor, and optimize data pipelines and infrastructure by analyzing performance metrics, identifying bottlenecks, and implementing efficiency and scalability improvements.
  • Collaborate with business analysts, data scientists, and DevOps engineers on successful data platform implementations.
  • Continuously learn and adapt to developments in big data technologies and best practices.
  • Take end-to-end ownership of data architecture delivery from vision through delivery and value realization.

About the Company

Capgemini

Global consulting, technology services, outsourcing

Capgemini provides consulting, technology services, and outsourcing to help organizations transform digitally. Its offerings include strategy and transformation consulting, system integration, application development, IT infrastructure management, and managed IT operations. It differentiates itself with a global presence in over 50 countries and a focus on applying AI, cloud, and cybersecurity to real business problems. Its goal is to help clients navigate digital transformation and improve efficiency and innovation through tailored, contract-based or managed services.

Company size
10,001+
Company stage
IPO
Headquarters
Paris, France
Founded
1967

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