2 months ago
Madrid, SpainMid Level / Senior
Responsibilities
- Design, build, and maintain ETL/ELT pipelines.
- Automate data ingestion, transformation, and reporting processes.
- Maintain data solutions and support the production deployment of models.
- Develop and evolve the MLOps framework.
- Manage data governance and quality, including documentation, lineage, security, compliance, and monitoring.
- Optimize the performance of pipelines, databases, and applications.
- Define testing, quality, governance, and data design best practices with other Data Engineers.
Requirements
- University degree in Computer Engineering or equivalent programming level.
- 3–4 years of experience.
- Experience with ETL/ELT processes and pipeline orchestration.
- Strong SQL and Python skills, or a similar data-oriented programming language.
- Experience with Docker, Kubernetes, and CI/CD pipelines.
- Knowledge of data governance, security, privacy, GDPR, and data lineage.
- Fluent English.
- Availability to work in a hybrid model in Madrid.
Benefits
- Continuous training through platforms including Coursera, Udemy, Pluralsight, Harvard Manager Mentor, and Education First language courses.
- Flexible compensation plan including medical insurance, transportation, training, restaurant card or meal subsidy, and childcare.
- Life and accident insurance.
- 24 vacation days, 2 personal days, December 24 and 31 off, and the option to purchase up to 7 additional vacation days annually.
- Hybrid work based in Madrid.
Tech Stack
Categories
Data Engineering
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.