About this role
Writing data pipelines to power cloud compute economics and sales compensation makes up a core part of the daily routine for this Analytics Engineer at Modal in New York. The data team focuses on building self-serve tools and driving business strategy by tracking company goals and supporting evidence-backed decisions. This newly expanding team partners closely with other departments as a trusted data adviser, delivering strategic analysis and consulting while developing modern analytics workflows.
Modal builds infrastructure for AI workloads, providing instant GPU access and container orchestration for customers such as DoorDash and Suno. The person stepping into this role will create foundational datasets for both human users and AI tools, tracking product use cases and external customer reporting. Ideal candidates bring strong communication skills, exceptional attention to detail, and the ability to translate data reporting into tangible business impact.
What you will do
- Contribute to building a modern analytics stack that supports AI-driven self-serve analysis, key metrics tracking, and external customer reporting.
- Influence work on new products like LLM Inference Endpoints through product analytics tracking.
- Identify millions of dollars of cost savings and optimization across tools and financial operations.
- Write data pipelines that power the operations of the business, such as cloud compute economics or sales comp.
- Create foundational datasets that can be used by people and AI tools to answer questions around product use cases, financial reporting, and marketing campaigns.
What you need
- Demonstrate fluency in SQL and proficiency in Python.
- Bring professional experience with at least two specified tools including Snowflake, dbt, dlt, Modal, Hex, or Posthog.
- Possess the ability to extend work beyond standard data reporting into measurable action and impact.
- Maintain high attention to detail across all engineering and analytical tasks.
- Communicate with excellent precision and clarity.
- Show strong personability and relationship-building skills.
Nice to have
- Experience with AI products, especially LLM inference and sandboxes
- Experience in fin ops, fraud, sales ops, or risk, especially in the context of AI (e.g. token cost optimization)
- Project management skills
- Strong presence in the data community online and offline
Skills and tech stack
Questions candidates ask
What is the compensation range for this role?
The salary for this position is listed as $150K – $250K. The company recently raised a Series C funding round and crossed $300M+ ARR.
Where is the job located?
The role is located in New York. Modal operates as an infrastructure provider for AI workloads from this location.
What tools and technologies will I use?
The tech stack includes SQL, Python, Snowflake, dbt, dlt, Modal, Hex, and Posthog. These tools support self-serve AI analytics and data pipeline operations.
What is the primary mission of the data team?
The mission of the Modal Data team is to make it easy to track company goals, make evidence-backed decisions, and prioritize the right work. This is achieved via self-serve AI analytics tools and embedding with teams as a data adviser.