22 days ago
Wrocław, Poland +3 moreStaff+
Responsibilities
- Create architectures for systems processing large and unstructured datasets, including data lake and streaming architectures.
- Design modern data warehouse and big data solutions in cloud and continuous integration/continuous delivery environments.
- Design data models and document data flows.
- Support the team as a technical leader and ensure compliance with software development standards and best practices.
Requirements
- Experience as an architect and/or technical leader on cloud or big data projects involving data processing and visualization across different SDLC phases.
- Practical commercial-project experience with AWS, Azure, or GCP services covering storage, compute, serverless, networking, and DevOps.
- Familiarity with several listed data, cloud, streaming, analytics, and infrastructure technologies.
- Basic command of at least one of Python, Scala, Java, or Bash.
Benefits
- Yearly financial bonus, private Medicover medical care, preferential additional healthcare packages, life insurance, and access to the NAIS benefits platform.
- Access to more than 70 training tracks with certification opportunities and learning platforms including NEXT, Education First, Pluralsight, TED Talks, Coursera, and Udemy Business.
- Hybrid working after onboarding, with office and work-from-home options and a home office package.
Tech Stack
Amazon RedshiftApache BeamApache KafkaApache SparkAWSAzureBashDatabricksGoogle BigQueryGoogle Cloud PlatformJavaPythonScalaSnowflakeTerraform
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.