GCP Data Platform Engineer

Description

The company is a global partner for AI-first digital transformation and engineering, with over 25 years in the field, around 5,000 staff and teams in 16 countries.

It focuses on artificial intelligence, data and cloud, intelligent automation and digital products, and builds scalable products, platforms and data-driven solutions.

The CEE team has close to 1,000 specialists who deliver applications, data platforms and AI solutions for a range of well-known clients, using AWS, Azure, GCP, Databricks and Snowflake.

The team values engineering quality, a consulting approach and ongoing learning and knowledge sharing.

Responsibilities

• Build, run and improve CI/CD pipelines.
• Set up shared CI/CD templates and reusable delivery components so repositories follow the same standards.
• Create and refine deployment automation.
• Design and put in place ways to store and distribute artifacts.
• Strengthen release management and software delivery workflows.
• Help manage Docker images and the workflows that deploy them.
• Support runtime environments running on Kubernetes.
• Remove manual steps from platform engineering work through automation.
• Move Python repositories from Poetry or setuptools to UV.
• Help keep software delivery governed, traceable and repeatable.
• Work with engineering teams to apply DevOps practices.
• Write and update technical documentation.

Requirements

• Strong commercial experience in DevOps, platform engineering or cloud engineering.
• Experience designing and maintaining CI/CD pipelines.
• Experience building reusable CI/CD templates and automation frameworks.
• Solid grasp of Git-based development workflows.
• Hands-on work 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 the infrastructure and application lifecycle.
• Strong communication and documentation skills.
• Experience with UV, including moving repositories from Poetry or setuptools to it.
• Familiarity with Google Cloud Platform and Google Cloud Storage.
• Familiarity with Apache Airflow, dbt, Dataproc or BigQuery.
• Experience supporting enterprise-scale data platforms.
• Experience applying software delivery governance standards.
• Experience in banking, financial services or other regulated industries.

Conditions

The hiring process runs in stages: CV review, HR call, interview, client interview, then a decision.