Data Engineer

About Us

Modal provides the infrastructure foundation for AI teams. With instant GPU access, sub-second container startups, and native storage, Modal makes it simple to train models, run batch jobs, and serve low-latency inference. We have thousands of customers who rely on us for production AI workloads, including Lovable, Scale AI, Substack, and Suno.

We're a fast-growing team based out of NYC, SF, and Stockholm. We've hit 9-figure ARR and recently raised a Series B at a $1.1B valuation. Our investors include Lux Capital, Redpoint Ventures, Amplify Partners, and Elad Gil.

About Modal Data

Working at Modal means joining one of the fastest-growing AI infrastructure organizations at an early stage, with many opportunities to grow within the company. 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.

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.

AI is changing everything about work, and we believe Data teams are even more impacted than the average team:

• Most users can truly self-serve now with AI analyst tools, which has collapsed the pure data analyst role

• Tools like Claude Code have made it possible for analytics engineers to go lower down the stack and take on traditionally data engineering projects

In the spirit of this vision, the scope of this role will include all parts of the data stack: data engineering, analytics engineering, and data analysis (roughly in order of importance).

The Role

You’ll work with everyone across the org including Product, Engineering, GTM, Finance, Business Operations, and the Exec Team. Your work will directly impact how teams and the overall company make decisions to make Modal as successful as possible.

If Modal were a professional basketball team, you are the stats guy in the back office. You measure the performance and impact of every position, helping managers decide where to invest more and motivating everyone to play at their best. You’re not handling the ball in the big game, but you’re everyone’s favorite support staff.

What you’ll do

• Contribute to building the most modern analytics stack in Data today to support AI-driven self-serve analysis, key metrics tracking, and customer reporting

• Influence work on new products like Sandboxes through product analytics tracking

• Write data pipelines that enrich our understanding of our business, especially on our cloud economics

• Create foundational datasets that can be used by people and AI tools to questions around product use cases, financial reporting, and marketing campaigns

What you should have

• SQL fluency, Python proficiency

• Professional experience with at least 3 of the following tools: Snowflake, dbt, dlt, Modal, Hex, Posthog, Segment

• Broad interest in going deep technically (like setting up Postgres CDC replication), all the way up to building analysis for high-level execs (like writing board decks)

• Extremely detail-oriented e.g. making sure your revenue query handles every distinct invoice line item

• Excellent communicator; people don’t trust data they trust people, so building relationships is essential to being successful, and that starts with precise and consistent communication

Nice to have

• Experience with major clouds like AWS, GCP, or Azure particularly on the billing side

• Strong presence in the data community online and offline

• AI practitioner experience, especially around building coding agents or LLM inference