> Markdown version of [/jobs/ext/4609492-analytics-engineer](https://www.wearedevelopers.com/jobs/ext/4609492-analytics-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Analytics Engineer - **Company:** Modal Labs - **Location:** San Francisco, CA, United States - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Catalyst (Software), Cloud Computing, Encodings, Python (Programming Language), Open Source Technology, SQL Databases, Graphics Processing Unit (GPU), Snowflake, Juniper, Luigi, Data Analytics, Model Inference, Data Pipelines - **Published:** November 6, 2026 - **Apply:** https://www.careerbuilder.com/job-details/analytics-engineer-san-francisco-ca--90b032ed-d976-4474-828b-7ff3f628f10a ## About the Role SLICE (Simulation Language with Integrated Circuit Emphasis), Artificial Intelligence (AI), Cloud Computing, GPU (Graphics Processing Unit), Juniper Networks M-Series, Academic Research, Open Source, Business Strategy, Establish Priorities, Strategic Analysis, * SQL fluency, Python proficiency * Professional experience with at least 2 of the following tools: Snowflake, dbt, dlt, Modal, Hex, Posthog * Ability to extend their work beyond just data reporting and into action and impact * High attention to detail * Excellent and precise communicator * 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 ## Description Our customers include category-defining companies like Lovable, Ramp, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so its simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. Weve crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g.,Seaborn,Luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. About Modal Data: We're growing our Data team and are looking for our first few key hires to build self-serve data tools and drive business strategy in the right direction. 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. We do this via: * Self-serve AI analytics tools (Hex, Snowflake) * Embedding with teams as a "data adviser", providing strategic analysis and consulting What Youll Do: * Contribute to building the most modern analytics stack in Data today to support 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 our tools and financial operations * Write data pipelines that power the operations of our business, such as our 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