Data Platform Engineer

Xebia is a global tech company with over 1,000 experts delivering work across cloud, data, and software. The company originated from two Polish companies, PGS Software and GetInData, pioneers in Big Data. Xebia works on projects in fintech, e-commerce, aviation, logistics, media, and fashion, helping clients build scalable platforms, data and AI solutions, and applications. Clients include McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, and InPost. Xebia uses modern open-source stacks and is a trusted partner of Databricks, dbt, Snowflake, Azure, GCP, and AWS, being the first AWS Premier Partner in Poland.

• Strong experience with Python for building data-related applications and services
• Background in data engineering or working with data/analytics platforms
• Very good knowledge of Kubernetes, including deployment, operations, and troubleshooting
• Hands-on experience with Docker and Helm
• Experience working with Git-based workflows (e.g., GitLab)
• Solid understanding of Linux-based environments
• Ability to work across development and infrastructure domains
• Experience with big data technologies such as Spark or HDFS
• Familiarity with SQL engines (e.g., Trino)
• Experience operating open-source data tools in production environments
• Understanding of CI/CD practices in platform or engineering teams
• Good communication skills and strong sense of ownership
• Good command of Polish (C1) and English (minimum B2)
• Practical experience using AI-powered assistants (e.g., Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery

Nice to have:

• Familiarity with tools such as Airflow, MLflow, or Superset
• Experience with platform and DevOps tools (e.g., ArgoCD, HashiCorp Vault)
• Knowledge of data governance or security tools (e.g., Apache Ranger, metastore solutions)
• Experience with frameworks such as FastAPI or Streamlit
• Previous experience transitioning from a data engineering role into a platform-focused role
• Experience applying GenAI in a structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work
• Interest in and familiarity with emerging AI-driven practices (e.g., agent-based workflows, automation patterns, AI-augmented development) with willingness to explore beyond standard approaches

• Designing, deploying, and maintaining applications running on Kubernetes
• Integrating open-source components into a unified analytics platform
• Developing internal services and tools in Python (e.g., FastAPI, Streamlit)
• Managing deployments using Helm, Docker, Git (GitLab), and ArgoCD
• Supporting and evolving tools used by analysts and data scientists (Airflow, JupyterHub, Superset, MLflow, Trino)
• Ensuring platform stability, scalability, and security
• Collaborating closely with data, analytics, and infrastructure teams
• Participating in architectural decisions and technology choices

Work from the European Union region and a work permit are required.