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Capgemini

Global consulting, technology services, outsourcing

Data Architect - Databricks Focus

Data EngineeringUpdated on Nov 14
Full-timeLisbon, Portugal

About the Job

Requirements

  • At least 5 years of experience in data architecture and/or data engineering, with hands-on experience in modern data platforms.
  • Strong experience with Databricks implementations, including architecture and delivery, Delta Lake, and governance concepts such as Unity Catalog.
  • Strong knowledge of lakehouse architectures and data warehousing concepts.
  • Strong knowledge of streaming and batch design patterns.
  • Strong knowledge of performance tuning and cost optimization in distributed data processing.
  • Strong knowledge of data governance and security patterns at scale.
  • Experience designing solutions on at least one major cloud (Azure, AWS, or Google Cloud) and integrating with cloud-native services.
  • Fluency in spoken and written Portuguese and English.
  • Databricks certification(s) and experience with Unity Catalog operating models are required.

Responsibilities

  • Own the architecture of Databricks-based solutions from discovery through delivery, ensuring scalability, maintainability, and performance.
  • Define and implement lakehouse patterns using Databricks, including Delta Lake and Unity Catalog, enabling analytics and artificial intelligence and machine-learning workloads.
  • Design batch and streaming data ingestion and transformation pipelines using best practices for reliability, observability, and service-level agreement management.
  • Establish standards for data modeling, dataset design, and domain-oriented data products where applicable.
  • Drive security, governance, and compliance, including access control, data privacy, auditing, lineage, and catalog strategies such as Unity Catalog and integration with enterprise identity and access management.
  • Provide technical leadership during delivery by unblocking teams, handling architectural trade-offs, and guiding performance and cost tuning of clusters, job patterns, and optimization.
  • Define DataOps and MLOps-adjacent practices as needed, including continuous integration and continuous delivery, testing strategies, environment promotion, and monitoring.
  • Support pre-sales and commercial initiatives through solution architecture, technical proposal content, effort estimation, delivery approach, and client technical workshops.
  • Work closely with cloud teams to integrate Databricks with AWS, Azure, or Google Cloud services, including storage, networking, security, and orchestration tools.

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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