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Lead Data Architect
Booksy
HybridHybrid
Original Job Summary
About the Role
A career at Booksy means you’re part of a global team focused on empowering entrepreneurs and helping people feel fantastic every day. As a Lead Data Architect (Governance) reporting to the Director of Analytics, you will design the structures, standards, and systems that transform raw data into a high-performance analytical ecosystem.
Key Responsibilities
- Design and build data warehouses using dimensional modeling (Kimball methodology).
- Implement solutions on Google Cloud Platform with BigQuery optimization and cost management.
- Develop advanced SQL transformations and production-level dbt pipelines.
- Build semantic layers with LookML in Looker, ensuring scalability and efficiency.
- Establish and enforce data governance standards with technical architecture.
What You Bring
You have hands-on experience with data warehousing, cloud infrastructure, and robust data governance. Your systems-thinking mindset and technical expertise across tools like BigQuery, dbt, and Looker will empower teams by ensuring data integrity from source to dashboard.
Benefits & Perks
- Flexible working hours and remote work options within your country.
- Be part of the world’s fastest growing beauty marketplace.
- International environment with teams in 6 countries.
- A welcoming, inclusive team that supports your growth.
Key skills/competency
- Data Warehousing
- Dimensional Modeling
- Google Cloud Platform
- BigQuery
- SQL
- dbt
- LookML
- Data Governance
- Metadata Management
- Systems Thinking
How to Get Hired at Booksy
🎯 Tips for Getting Hired
- Customize your resume: Highlight data architecture projects and cloud experience.
- Emphasize technical skills: Showcase SQL, dbt, and LookML expertise.
- Show systems thinking: Detail end-to-end data lifecycle accomplishments.
- Prepare case studies: Discuss solving ambiguity and technical challenges.
📝 Interview Preparation Advice
Technical Preparation
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Review Kimball methodology fundamentals
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Learn BigQuery optimization strategies
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Practice advanced SQL and dbt pipelines
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Study LookML and Looker configurations
Behavioral Questions
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Describe handling ambiguity in projects
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Explain prioritization in chaotic situations
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Discuss cross-team collaboration examples
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Share experiences with remote communication