Lead Data Engineer (Platform)

Tasks

• Conduct code and design reviews for platform components
• Contribute documentation developer guides and enablement materials
• Define and enforce engineering standards for testing code quality deployment and documentation
• Define and evolve platform architecture decisions
• Design and implement CI CD pipelines and automation frameworks
• Design build maintain scalable data engineering frameworks and platform utilities
• Develop and maintain AI engineering assets coding guidelines prompt frameworks agent configurations
• Develop reusable patterns templates and abstractions
• Eliminate manual or repetitive processes through automation and tooling
• Ensure platform tooling meets security compliance and operational requirements
• Integrate AI assisted development tools into engineering workflows
• Investigate and resolve framework level issues deployment failures dependency conflicts production incidents
• Lead development and operational support of core data transformation frameworks
• Monitor platform health performance and adoption
• Partner with engineering teams to identify pain points and deliver platform improvements
• Serve as main technical point of contact for platform and framework queries
• Support onboarding and enablement for teams adopting platform tooling

Perks/Benefits

• 24 days vacation
• Annual company events
• Challenging projects
• Cool colleagues
• Education program
• Events
• Free beverages
• Honest feedback
• Private health insurance
• Wellbeing program

Skills/Tech-stack

Alerting | Apache Spark | Azure DevOps | CI/CD | DBT Core | Data Quality | Data Quality Testing | Databricks | Delta Lake | Git | GitHub Actions | GitLab CI | Infrastructure as Code | Integration Testing | Lakehouse | Logging | Monitoring | Prompt engineering | Prompt frameworks | Python | Quality testing | SQL | Terraform | Unit Testing | Unity Catalog | Version control | “as-code”