GCP Data Engineer

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 Millennium, ING, Play, Edenred, Arabian Drilling, FedEx, Leroy Merlin, Truecaller, Volotea, Schmitz Cargobull, 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, developing, and optimizing ETL/ELT pipelines on Google Cloud Platform.

Optimizing Spark workloads running on Dataproc and Dataproc Serverless.

Implementing workload-routing strategies and cost-optimization mechanisms.

Designing and maintaining data-ingestion processes for Bronze, Silver, and Gold layers.

Organizing and managing raw-data structures in Google Cloud Storage.

Designing and implementing event-driven orchestration using Pub/Sub and Apache Airflow.

Developing, maintaining, and optimizing Airflow DAGs and orchestration frameworks.

Implementing data reprocessing and backfill capabilities.

Consolidating related processing workflows into reusable orchestration patterns.

Extending and improving metadata-driven generators and platform tooling.

Supporting artifact generation, regeneration, and distribution processes.

Improving observability, reliability, and operational support for data pipelines.

Collaborating with platform, analytics, and DevOps teams on architecture and implementation decisions.

Your profile:

Strong commercial experience building and operating data platforms on Google Cloud Platform.

Hands-on experience with Dataproc and Apache Spark.

Experience designing and developing ETL/ELT pipelines.

Experience with BigQuery and Google Cloud Storage.

Strong SQL and Python skills.

Experience optimizing data-processing performance and cloud costs.

Experience designing ingestion frameworks and reusable data-processing components.

Understanding of data-platform architecture patterns, including Bronze/Silver/Gold layers.

Experience troubleshooting and supporting production data pipelines.

Strong hands-on experience with Apache Airflow.

Experience designing, implementing, and maintaining complex DAGs

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

Recruitment Process:

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