2 months ago
Lisbon, PortugalMid Level
Responsibilities
- Design, develop, and maintain scalable data pipelines using Python, PySpark, and Databricks.
- Build reusable data processing and transformation frameworks following engineering best practices.
- Collaborate with Data Scientists, Data Analysts, and Software Engineers to deliver scalable data solutions.
- Support data modeling for analytical and operational use cases.
- Deploy and manage data workloads in Azure Cloud environments.
- Contribute to CI/CD pipelines and deployment automation using Azure DevOps.
- Maintain code quality, testing, version control, and documentation standards.
Requirements
- 4+ years of experience in Data Engineering or a similar role.
- Strong hands-on experience with Python, PySpark, and Databricks.
- Proven experience designing and maintaining production-grade data pipelines.
- Solid understanding of Azure Cloud environments.
- Additional experience with Azure DevOps, Git, version control systems, CI/CD pipelines, and data modeling techniques.
- Strong analytical, problem-solving, communication, collaboration, and independent-working skills.
Benefits
- Hybrid work arrangement.
- Multicultural, inclusive, and supportive team environment promoting work-life balance.
- Career growth programs and access to training and certifications in current technologies.
- Opportunities to work on national and international projects.
- Health and life insurance.
- Referral program with bonuses for talent recommendations.
- Great office locations.
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.