Senior 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. 

We are looking for a Senior Data Platform Engineer to join a cloud transformation and migration project delivered for our international client. The project focuses on evolving an existing cloud platform from an initial MVP into a scalable environment that supports self-service capabilities, large-scale migration, infrastructure automation, and AI enablement.

The initiative runs from June 2026 to June 2027 and consists of multiple parallel delivery streams. The focus is on building reusable cloud infrastructure and platform capabilities that enable engineering teams to deploy, operate, and scale their workloads efficiently.

You will collaborate closely with data engineers, data architects, and delivery management, contributing to platform reliability, automation, governance, and the continuous improvement of cloud infrastructure in a complex enterprise environment.

You will be:

• designing, building, and maintaining cloud platform solutions using Google Cloud Platform (GCP),
• developing and managing reusable Infrastructure as Code using Terraform,
• building and enhancing CI/CD pipelines to support reliable, automated deployments,
• driving infrastructure automation and self-service capabilities for engineering teams,
• supporting cloud migration activities across multiple parallel delivery streams,
• designing scalable, reliable solutions based on cloud-native architecture and distributed systems,
• improving platform observability, monitoring, logging, performance, and operational reliability,
• applying cloud governance, security, and cost-optimization best practices,
• collaborating with data engineers, data architects, and delivery teams to align platform capabilities with project needs,
• contributing to engineering standards, reusable patterns, and continuous platform improvement,
• supporting the evolution of the platform toward greater automation, developer enablement, and AI-assisted capabilities.

Your profile:

• strong hands-on experience with Google Cloud Platform (GCP),
• solid experience with Terraform and Infrastructure as Code,
• proven experience building and maintaining CI/CD pipelines,
• strong background in infrastructure automation and cloud platform engineering,
• understanding of distributed systems and cloud-native architecture,
• experience working in complex enterprise environments with multiple parallel delivery streams,
• strong problem-solving skills and an ownership-oriented mindset,
• ability to communicate effectively and collaborate across technical and delivery teams.

• experience with platform engineering or internal developer platforms,
• exposure to data platform technologies and architectures, such as BigQuery, Kafka, and data pipelines,
• knowledge of Kubernetes and containerization,
• experience supporting large-scale cloud migrations or transformation programs,
• familiarity with monitoring, logging, and observability tools,
• understanding of cloud security and infrastructure governance best practices.

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

Nice to have:

• experience building self-service platforms and developer enablement capabilities,
• familiarity with AI enablement and advanced infrastructure automation use cases,
• GCP certifications,
• experience working with international and distributed engineering teams.

Recruitment Process:

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