Lead Data Platform Engineer

Xebia; Poland; On-site; PLN 304,000 - 434,000; Full time

Job summary

Xebia seeks a data platform engineer to design and build scalable data products, tooling, and templates in a modern cloud environment.

You will collaborate with platform, data engineering, analytics, and ML teams to evolve Airflow/Cloud Composer pipelines, IaC modules, and developer tooling, while ensuring quality and observability.

Proficiency in Polish and English, strong Python and GCP experience, and EU work eligibility are required; remote work within the EU is supported.

Qualifications

• Strong Python development experience in a cloud data setting.
• Practical Google Cloud Platform experience and BigQuery
• Hands-on with Apache Airflow or Cloud Composer
• IaC practices with Terraform and GitOps mindset
• Knowledge of CI/CD and modern software delivery
• Understanding of data engineering concepts and data product lifecycle
• Experience with PySpark or Spark ecosystem
• Familiarity with FastAPI and modern Python tooling
• Proficient Polish and English communication skills
• Experience in Agile development environments

Responsibilities

• Designing and developing tools that standardize and automate Data Platform operations.
• Building and maintaining internal CLI tools for platform and Data Product management.
• Developing and evolving Data Product templates using best practices.
• Designing and implementing visualizations and insights within Backstage.
• Collecting platform usage metrics, audit data, and adoption statistics.
• Designing Agentic AI workflows and developer-assistance capabilities.
• Developing reusable AI skills and automation components for data products.
• Creating distribution, lifecycle management, and monitoring for AI skills.
• Maintaining a shared Apache Airflow platform on Cloud Composer.
• Building reusable libraries, operators, and components for Airflow DAGs.
• Developing and maintaining IaC assets and Terraform modules.
• Contributing to GitOps adoption using Backstage, GitHub, ArgoCD, Crossplane.
• Collaborating with platform, data engineering, analytics, and ML teams to improve usability.

Skills

Python development

GCP

BigQuery

Airflow / Cloud Composer

Terraform / IaC

GitOps

CI/CD

Agile development

Polish language

English language

Data engineering concepts

PySpark

FastAPI / Python tooling

Tools

Cloud Composer

Backstage

Terraform

GitHub

ArgoCD

Crossplane

Dataproc

dbt

Kedro

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