17 days ago
Wrocław, Poland +4 moreEntry Level
Responsibilities
- Design and implement large-scale data processing solutions using Databricks.
- Build and enhance data pipelines with Python and cloud-native tools.
- Collaborate with solution architects to define and maintain data engineering best practices.
- Ensure data consistency, security, and scalability in cloud-based environments.
Requirements
- Strong data engineering experience with at least 1 year of hands-on Databricks expertise.
- Strong Python experience for automation and data transformation.
- Experience with at least one major cloud platform: AWS, Azure, or GCP.
- Strong communication and English language skills.
- Preferred qualifications include SQL query optimization, data modeling, DevOps and CI/CD familiarity, Terraform or Bicep, Kafka or Spark Streaming, Data Lake, Snowflake or Synapse, PySpark, and relevant Databricks or cloud certifications.
Benefits
- Medical care with Medicover, private life insurance, a Sports card, and access to Capgemini Helpline therapeutic support.
- More than 70 training tracks with certification opportunities through the NEXT platform.
- Free access to Education First, Pluralsight, TED Talks, Coursera, and Udemy Business learning materials and training.
- Stable and supportive work culture recognized as Top Employer Poland 2024.
- Opportunities to work with current technologies and platforms alongside global enterprise clients.
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.