Mid/Senior Data Engineer (GCP)

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:

designing, building, and maintaining scalable data pipelines supporting the migration to BigQuery,

developing ingestion frameworks and transformation pipelines, with a strong focus on data quality,

orchestrating, monitoring, and optimising data processing workloads,

delivering production-grade data products that serve reporting, analytics, and business intelligence needs,

collaborating with Analytics Engineers, Architects, and business stakeholders to ensure successful migration and long-term platform sustainability.

Your profile:

strong Python and SQL skills,

hands-on experience with Google BigQuery,

experience building and maintaining ETL/ELT pipelines,

experience working with structured and semi-structured data,

strong data modeling and schema design skills,

experience with workflow orchestration tools such as Airflow, Cloud Composer, or similar,

experience with Git-based version control and CI/CD practices,

understanding of data quality, validation, testing, and monitoring approaches,

understanding of modern cloud-native data architectures,

hands-on experience with dbt is a big plus.

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

Nice to have:

experience optimising and tuning BigQuery workloads,

experience with data platform modernisation or migration projects,

knowledge of Infrastructure as Code (IaC) concepts and tools,

experience integrating with external APIs and ingesting third-party data,

understanding of data governance, lineage, and metadata management practices,

experience with monitoring, observability, and operational support of data platforms,

familiarity with Looker or other BI/analytics consumption layers.

Recruitment Process:

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