Lead Data Platform Engineer

Project Description The Lead Data Platform Engineer plays a crucial role in developing and enhancing a cloud-native Data Platform for a large-scale e-commerce marketplace. The primary objective is to improve developer experience and streamline data processes through automation and standardization, ultimately enabling data-driven decisions and supporting rapid product growth.

Responsibilities

• Design and develop tools that standardize, automate, and simplify Data Platform operations.
• Build and maintain internal CLI tools for common 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 that standardize work with data products and data assets.
• Create mechanisms for distribution, lifecycle management, and monitoring of AI skills.
• Maintain and enhance a shared Apache Airflow platform based on Cloud Composer.
• Build reusable libraries, operators, and common components for Airflow DAG development.
• Develop and maintain infrastructure-as-code assets and Terraform modules.
• Contribute to GitOps adoption initiatives using tools such as Backstage, GitHub, ArgoCD, and Crossplane.
• Collaborate with platform, data engineering, analytics, and machine learning teams to improve platform usability and engineering efficiency.

Requirements

• 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.

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.