Lead Data Platform Engineer

Xebia Group; Polska; On-site; PLN 180,000 - 320,000; Full time

Job summary

Xebia Group is seeking a Data Platform Engineer to design and deliver tooling and pipelines on GCP, enabling scalable data products and AI-enabled workflows. You will build internal tooling, templates, and visualizations with Airflow/Cloud Composer, Backstage, and Terraform, while collaborating with data engineering, analytics, and ML teams.

The role requires strong Python, BigQuery, PySpark, and modern tooling expertise, plus fluent Polish and English.

Qualifications

• Strong experience with Python development.
• Hands-on experience with Google Cloud Platform (GCP).
• Practical experience with BigQuery and cloud-based data platforms.
• Experience with Apache Airflow, preferably Cloud Composer.
• Experience building platform engineering or internal self-service solutions.
• Knowledge of Infrastructure as Code and Terraform.
• Experience with GitOps and modern software delivery practices.
• Good understanding of data engineering and Data Product lifecycle management.
• Experience with PySpark and/or Apache Spark ecosystems.
• Familiarity with FastAPI, Pydantic, and modern Python tooling.
• Knowledge of CI/CD processes and source control best practices.
• Experience working in Agile development environments.
• Strong problem-solving skills and ability to work independently.
• Effective communication and cross-functional collaboration.
• Proficiency in Polish and English.

Responsibilities

• Design and develop tools that standardize, automate, and simplify Data Platform operations.
• Build and maintain internal CLI tools for platform and Data Product management tasks.
• Develop and evolve Data Product templates based on modern data engineering practices.
• Design and implement visualizations and operational insights within Backstage.
• Collect and analyze platform usage metrics, audit data, and adoption statistics.
• Design and implement Agentic AI workflows and developer-assistance capabilities.
• Develop reusable AI skills and automation components to standardize data products.
• Create mechanisms for distribution, lifecycle management, and monitoring of AI skills.
• Maintain and enhance a shared Apache Airflow platform (Cloud Composer).
• Build reusable libraries, operators, and components for Airflow DAG development.
• Develop and maintain infrastructure-as-code assets and Terraform modules.
• Contribute to GitOps adoption initiatives using Backstage, GitHub, ArgoCD, Crossplane.
• Collaborate with platform, data engineering, analytics, and ML teams to improve usability and efficiency.

Skills

Python

GCP

BigQuery

Apache Airflow

Terraform

GitOps

PySpark

FastAPI

CI/CD

Agile

Polish & English

Tools

Cloud Composer

Backstage

Dataproc

dbt

Job description

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 and developing tools that standardize, automate, and simplify Data Platform operations.
• Building and maintaining internal CLI tools for common platform and Data Product management tasks.
• Developing and evolving Data Product templates based on modern data engineering practices.
• Designing and implementing visualizations and operational insights within Backstage.
• Collecting and analyzing platform usage metrics, audit data, and adoption statistics.
• Designing and implementing Agentic AI workflows and developer-assistance capabilities.
• Developing reusable AI skills and automation components that standardize work with data products and data assets.
• Creataing mechanisms for distribution, lifecycle management, and monitoring of AI skills.
• Maintaining and enhancing a shared Apache Airflow platform based on Cloud Composer.
• Building reusable libraries, operators, and common components for Airflow DAG development.
• Developing and maintaining infrastructure-as-code assets and Terraform modules.
• Contributing to GitOps adoption initiatives using tools such as Backstage, GitHub, ArgoCD, and Crossplane.
• Collaborating with platform, data engineering, analytics, and machine learning teams to improve platform usability and engineering efficiency.

Your profile:

• Strong commercial experience with Python development.
• Hands-on experience with Google Cloud Platform (GCP).
• Practical experience with BigQuery and cloud-based data platforms.
• Experience with Apache Airflow, preferably Cloud Composer.
• Experience building platform engineering, developer tooling, or internal self-service solutions.
• Knowledge of Infrastructure as Code practices and Terraform.
• Experience with GitOps principles and modern software delivery practices.
• Good understanding of data engineering concepts and Data Product lifecycle management.
• Experience with PySpark and/or Apache Spark ecosystems.
• Familiarity with FastAPI, Pydantic, and modern Python tooling.
• Knowledge of CI/CD processes and source control best practices.
• Experience working in Agile development environments.
• Strong problem-solving skills and ability to work independently.
• Effective communication skills and ability to collaborate with cross-functional teams.
• Professional proficiency in Polish and English.

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

Nice to have:

• Experience with Vertex AI or other GenAI platforms.
• Hands-on experience with GitHub Copilot, Copilot extensions, plugins, or AI-assisted development solutions.
• Experience developing Agentic AI workflows or AI automation capabilities.
• Knowledge of Backstage plugin development.
• Experience with Dataproc.
• Familiarity with dbt and Kedro.
• Experience with ArgoCD and Crossplane.
• Experience building observability, telemetry, or platform analytics solutions.
• Experience working in large-scale data environments supporting analytics and machine learning workloads.

Recruitment Process:

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