Modal
Analytics Engineer
About this role
Modal is seeking an Analytics Engineer to build self-serve data infrastructure and drive business insights for a rapidly growing AI infrastructure company. You'll develop pipelines, create foundational datasets, and partner with teams to optimize operations and track critical metrics.
What you'll do
- Build and maintain modern analytics infrastructure using Snowflake, dbt, and self-serve tools like Hex
- Develop data pipelines supporting cloud economics, sales operations, and financial reporting
- Create datasets for product analytics, customer insights, and business intelligence
- Identify cost optimization opportunities across infrastructure and operations
- Partner with product and business teams as a data advisor on strategic initiatives
- Track and report on product analytics for new offerings like LLM Inference Endpoints
What they're looking for
- SQL
- Python
- Snowflake
- dbt
- Data pipeline development
- Product analytics
- Business acumen and financial operations
- Communication and stakeholder management
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Modal
Modal builds a cloud platform for running large-scale AI workloads and infrastructure, enabling companies to deploy and optimize production machine learning systems. The company is hiring Forward Deployed Engineers to work directly with AI customers, Infrastructure Security Engineers to strengthen platform security, and Developer Relations Engineers to engage the developer community with technical content and best practices.
- Website
- modal.com
Likely interview questions
- Walk us through your experience building data pipelines at scale—what tools did you use and what challenges did you encounter?
- Tell us about a time you identified a significant cost saving or optimization. How did you approach it and what was the impact?