Lead Data Engineer (Platform)

Valtech is an experience innovation company that helps brands unlock new value in a digital world. They drive transformation for leading organizations including L’Oréal, Mars, Audi, P&G, Volkswagen, Dolby, and more. Valtech fosters a workplace where employees have support to thrive, grow, and innovate.

• Strong proficiency in Python for building frameworks, automation tooling and reusable components
• Hands-on experience with Databricks (including notebooks, workflows, jobs and Unity Catalog)
• Strong SQL skills and experience with distributed processing frameworks such as Apache Spark
• Deep experience with dbt Core, including project structure, models, tests, macros and deployment at scale
• Proven experience designing and maintaining CI/CD pipelines (e.g. GitHub Actions, Azure DevOps or GitLab CI)
• Experience with data engineering platform design, including scalable pipeline and workflow architectures
• Strong understanding of software engineering principles (DRY, SOLID, modular design)
• Experience working with version control systems and modern Git workflows
• Experience with cloud platforms (preferably AWS) and infrastructure-as-code concepts (e.g. Terraform)
• Experience implementing automated testing strategies (unit, integration, data quality)
• Strong understanding of platform monitoring, logging and alerting practices
• Experience writing technical documentation and developer-facing guidance
• Experience working in complex engineering environments with multiple teams

Nice to have:

• Experience with Databricks Asset Bundles (DAB) or similar deployment frameworks
• Experience integrating AI-assisted development tools (e.g. GitHub Copilot or similar) into engineering workflows
• Experience defining AI coding standards, agent configurations or prompt engineering frameworks
• Knowledge of Delta Lake and Lakehouse architecture patterns
• Experience working on large-scale platform engineering or developer platform teams
• Understanding of IAM, secrets management and security compliance in cloud environments
• Experience driving adoption of engineering platforms across multiple teams
• Strong communication and technical leadership skills

• Design, build, and maintain scalable data engineering frameworks and platform utilities used across engineering teams
• Develop reusable patterns, templates, and abstractions to standardise and accelerate delivery
• Define and evolve platform architecture decisions, ensuring scalability, maintainability and consistency
• Design and implement CI/CD pipelines and automation frameworks to improve engineering velocity
• Define and enforce engineering standards for testing, code quality, deployment and documentation
• Identify and eliminate manual or repetitive processes through automation and tooling improvements
• Integrate AI-assisted development tools into engineering workflows to improve productivity
• Develop and maintain AI engineering assets such as coding guidelines, prompt frameworks and reusable agent configurations
• Lead the development and operational support of core data transformation frameworks (including dbt Core at enterprise scale)
• Investigate and resolve framework-level issues, including deployment failures, dependency conflicts and production incidents
• Support onboarding and enablement of engineering teams adopting platform tooling
• Act as the main technical point of contact for platform and framework-related queries
• Partner with engineering teams to identify pain points and translate them into platform improvements
• Ensure platform tooling meets security, compliance and operational requirements
• Conduct and support code and design reviews across platform components
• Monitor platform health, performance and adoption, iterating based on feedback and metrics
• Contribute to documentation, developer guides and enablement materials to improve usability and adoption

This is a position based in Poland.