O pozici
Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions.
We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.
In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing.
Co budeš dělat
- seting up and configuring the data platform infrastructure in Azure and Databricks,
- designing and implementing CI CD and deployment pipelines for data workloads,
- establishing and managing environments (dev, test, prod),
- building and maintaining orchestration and scheduling mechanisms for data pipelines,
- ensuring platform scalability, reliability, and performance,
- collaborating closely with Data Engineers and Architects on platform design decisions,
- supporting automation and standardization of data platform operations.
Koho hledáme
- proven experience as a Platform Engineer, DevOps Engineer, or Data Platform Engineer,
- strong experience with Azure cloud Hands on experience with Databricks,
- experience with CI CD pipelines and infrastructure as code,
- experience working with data platforms (not only application infrastructure),
- understanding of distributed data processing environments,
- experience with orchestration tools or workflow engines (for example Argo or similar),
- experience supporting data pipelines and ingestion frameworks,
- knowledge of containerization and platform tooling (for example Docker, Kubernetes),
- experience setting up monitoring, logging, and alerting for data platforms,
- ability to work in integration heavy environments,
- practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery.
- Work from the European Union region and a work permit are required.
Benefity
- Nice to have:
experience with Salesforce or CRM based data ecosystems,
knowledge of security, governance, and access control mechanisms in cloud data platforms,
experience with performance optimization in distributed environments,
experience in enterprise or regulated industries,
certifications related to Azure or Databricks,
interest in and familiarity with emerging AI-driven practices (e.g. agen
