👉 Data Platform Engineer

🟣 You will be:

• 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.

🟣 Your profile:

• strong experience with Python, used 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 (min. 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 more 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 a willingness to explore and experiment beyond standard approaches.

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

🟣 Recruitment Process: CV review – HR Call – Interview – Client Interview – Decision

🎁 Benefits 🎁

✍ Development:

• development budget of up to 6,800 PLN,

• we fund certifications e.g.: AWS, Azure, ISTQB, PSM,

• access to Udemy, Safari Books Online and more,

• events and technology conferences,

• technology Guilds,

• internal training,

• Xebia Library,

• Xebia Upskill.

🩺 We take care of your health:

• private medical healthcare,

• multiSport card - we subsidise a MultiSport card,

• mental Health Support.

🤸‍♂️ We are flexible:

• flexible working hours,

• B2B or permanent contract,

• contract for an indefinite period.