Azure Data Enginer

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. 

You will be:

• developing and maintaining data ingestion pipelines from source systems to the raw data layer,


• onboarding new data sources into the data platform,


• contributing to the ongoing development and improvement of the Azure-based data platform,


• supporting and enhancing monitoring and orchestration of data workflows,


• participating in daily activities as a fully embedded member of the client’s internal data team,


• assisting with knowledge transfer from outgoing engineers to ensure a smooth transition,


• proactively identifying opportunities to improve reliability, performance, and maintainability of data pipelines.

Your profile:

• strong hands-on experience with Azure data platforms, including data ingestion, storage, and processing.


• solid understanding of data pipeline design, development, and maintenance,


• practical experience with ETL / ELT processes and data integration patterns,


• experience with Databricks,


• experience working with monitoring and orchestration of data workflows,


• ability to work independently within an existing team and take ownership of assigned tasks,


• very good communication skills in English,


• familiarity with cloud-native data architecture principles,


• experience supporting production data platforms with a focus on stability and operational excellence,


• ability to ramp up quickly in an existing environment with minimal disruption,


• 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.

Nice to have:

• previous experience in banking or financial services,


• exposure to regulated environments and data governance practices,


• experience working in distributed or nearshore teams,


• experience participating in or supporting knowledge transfer and transition phases,


• 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.

Recruitment Process:

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