What You'll Do
- Design, implement, and maintain data models using dbt within our cloud data warehouse, ensuring performance, cost efficiency, and alignment with business logic
- Own the semantic layer and metrics definitions for one or more of our core domains, ensuring consistency and high-quality data access across LightDash and other downstream tools
- Collaborate with other analytics engineers and data engineers to build and scale ELT workflows that ensure data freshness and reliability for mission-critical reporting
- Implement robust testing, documentation, and monitoring practice-you'll be a steward of data quality and governance across the platform
- Collaborate closely with product, marketing, and commercial analysts to translate complex business questions into scalable, production-ready data artifacts
- Partner with the data analysts and domain leadership to drive the rollout and adoption of self-service analytics, ensuring business users can trust and independently explore the data models you build
- Contribute to the evolution of our modern data stack, bringing curiosity and pragmatic judgment to new tools and approaches
Must Have
- Bachelor's/Master's degree in a quantitative field (statistics, economics, mathematics, computer science, or similar)
- 5+ years in analytics engineering, data engineering, or analytics roles with significant modeling responsibilities
- Strong SQL and data modeling skills, with demonstrated experience designing robust, scalable dimensional models
- Significant hands-on experience with dbt (Core or Cloud) for managing transformation logic, testing, and documentation
- Familiarity with cloud data platforms (BigQuery) and data orchestration tools (Airflow, Dagster, or similar)
- Experience working with modern BI platforms and semantic layers-LightDash experience is a strong plus
- Experience with self service analytics
- Track record of partnering with analysts and business stakeholders to translate requirements into well-structured data products
- Strong communication skills, with the ability to explain complex data concepts to diverse audiences
- Proactive self-starter who thrives on solving ambiguous problems and takes ownership from concept to production
Nice to Have
- Experience in marketplace, telecom, or travel/mobility businesses
- Background in B2C product companies with high-volume event data
- Experience building analytics engineering capabilities in low-maturity data environments
- Previous experience at a scale-up that went through hypergrowth
- Experience defining and governing company-wide KPIs and metric frameworks
Top Skills
What We Do
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