Senior Data Engineer

About the role

ABOUT E2B

E2B is a fast-growing Series A startup with over $37M in funding and 8-figure revenue. We are building the Agent Cloud and power the infrastructure behind AI labs and some of the most widely used consumer and enterprise agents, including Manus, Genspark, Lindy, Groq, and Artificial Analysis. Our team includes original authors of Firecracker, the AWS microVM technology powering Lambda, along with alumni of Cognition, JetBrains, Zapier, and Wish.

ABOUT THE ROLE

We’re looking for a Senior Data Engineer to build the data foundation that helps us understand our business and make better decisions.

You’ll turn data across our infrastructure, billing, and business systems into reliable pipelines and clearly defined datasets. You’ll join the engineering team, report to our Head of Engineering, and work closely with our Head of Finance as your primary partner initially. Over time, your work will support Growth, GTM, and other teams across E2B.

We have data and pieces of the foundation in place. You’ll help bring them together, establish the missing building blocks, and own the quality and usefulness of what we deliver.

You’ll have direct access to the people using your work and substantial ownership over how E2B’s data foundation develops. Your work will help teams answer important questions independently, spend less time reconciling numbers, and make decisions with confidence.

Responsibilities include:

- Build and operate pipelines that bring operational and business data into our warehouse, including sandbox usage, cloud infrastructure, billing, and accounting data.

- Create data models and shared metric definitions that teams can understand and use consistently.

- Establish testing, monitoring, reconciliation, and alerting to catch missing data, inconsistencies, and unexpected changes.

- Partner with Finance to turn business questions into dependable datasets, starting with usage, revenue, costs, and margins.

- Make data accessible for self-service analysis, reporting, and AI-assisted querying through clear structure and documentation.

- Work with engineering teams to improve source data quality and resolve issues from ingestion through downstream consumption.

- Make practical decisions about architecture and tooling, balancing immediate business needs with maintainability.

WHAT WE’RE LOOKING FOR

- Experience building and owning production data pipelines and warehouse models, including establishing foundations where systems were incomplete or fragmented.

- Strong SQL and Python skills, with sound software engineering practices around testing, version control, deployment, and monitoring.

- Experience with a cloud data warehouse such as BigQuery, Snowflake, or Redshift, and tools for data transformation and orchestration.

- A track record of working directly with business stakeholders, clarifying ambiguous requirements, and connecting technical work to business outcomes.