Data Engineer with Airflow

Who We Are

While Xebia is a global tech company, our journey in CEE started with two Polish companies – PGS Software, known for world-class cloud and software solutions, and GetInData, a pioneer in Big Data. Today, we’re a team of 1,000+ experts delivering top-notch work across cloud, data, and software. And we’re just getting started.

What We Do

We work on projects that matter – and that make a difference. From fintech and e-commerce to aviation, logistics, media, and fashion, we help our clients build scalable platforms, data and AI solutions, and cutting-edge applications to shape the future of tech. Our clients include McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more.

We value smart tech, real ownership, and continuous growth. We use modern, open-source stacks, and we’re proud to be trusted partners of Databricks, dbt, Snowflake, Azure, GCP, and AWS. Fun fact: we were the first AWS Premier Partner in Poland!

Beyond Projects

What makes Xebia special? Our community. We support tech communities, organize meetups (Software Talks, Data Tech Talks), and have a culture that actively support your growth via Guilds, Labs, and personal development budgets — for both tech and soft skills. It’s not just a job. It’s a place to grow.

What sets us apart? 

Our mindset. Our vibe. Our people. And while that’s hard to capture in text – come visit us and see for yourself.

• providing hands-on assistance with Airflow configuration, DAG design, scheduling, and troubleshooting,
• acting as a technical advisor for customer data engineering teams using diverse technology stacks,
• helping customers integrate Airflow with their existing data ecosystem (e.g. cloud data warehouses, transformation tools, infrastructure as code),
• supporting customers during initial platform adoption and production onboarding,
• toubleshooting complex Airflow-related issues and guiding customers toward stable, reliable solutions,
• collaborating with an internal project owner responsible for scope management, status tracking, and meeting facilitation.

• strong hands-on knowledge of Apache Airflow, including DAG development, scheduling, and operational concepts,
• professional experience with Python,
• experience supporting or working with data engineering platforms in a customer-facing or advisory role,
• ability to troubleshoot distributed systems and production issues,
• strong communication skills and customer empathy, especially in technical training and support scenarios,
• ability to work independently in a remote, distributed environment,
• practical understanding of Kubernetes and containerized environments,
• experience working with managed cloud services,
• familiarity with at least one modern data stack (e.g. Snowflake, dbt, Terraform),
• experience delivering technical workshops, training sessions, or enablement activities.
• ability to quickly learn new platforms and internal tooling,
• 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.

• experience with Airflow administration in production environments,
• exposure to infrastructure as code (Terraform or similar),
• familiarity with SQL and analytical data workflows,
• previous experience in customer support, reliability engineering, or platform engineering roles,
• experience working with enterprise customers during onboarding or adoption phases,
• 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.

CV review – HR call – Interview – Client Interview – Decision