GCP Data Platform 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:

design, implement, and maintain CI/CD pipelines,

standardize repositories using shared CI/CD templates and reusable delivery components,

develop and maintain deployment automation processes,

design and implement artifact storage and distribution mechanisms,

improve release management and software delivery processes,

support Docker image management and deployment workflows,

support Kubernetes-based runtime environments,

automate manual platform engineering activities,

migrate Python repositories from Poetry or setuptools to UV,

support governance, traceability, and repeatability of software delivery,

collaborate with engineering teams to implement DevOps best practices,

prepare and maintain technical documentation.

Your profile:

strong commercial experience in DevOps, Platform Engineering, or Cloud Engineering roles,

experience designing and maintaining CI/CD pipelines,

experience building reusable CI/CD templates and automation frameworks,

strong understanding of Git-based development workflows,

hands-on experience with Docker,

experience supporting Kubernetes environments,

experience automating build, release, and deployment processes,

experience managing software artifacts and release assets,

experience with Python packaging and dependency management,

understanding of infrastructure and application lifecycle management,

strong communication and documentation skills.

Nice to have:

experience with UV and migrating repositories from Poetry or setuptools to UV,

familiarity with Google Cloud Platform and Google Cloud Storage,

familiarity with Apache Airflow, dbt, Dataproc, or BigQuery,

experience supporting enterprise-scale data platforms,

experience implementing software delivery governance standards,

experience in banking, financial services, or other regulated industries.

Recruitment Process:

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