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E2B

Senior Data Engineer

Posted 28 Days Ago
In-Office
San Francisco, CA, USA
200K-250K Annually
Senior level
In-Office
San Francisco, CA, USA
200K-250K Annually
Senior level
Build and own production data pipelines, warehouse models, metric definitions, testing, monitoring, reconciliation, and alerting. Partner with Finance and other teams to create reliable datasets for usage, revenue, costs, margins, reporting, self-service analysis, and AI-assisted querying. Improve source data quality, investigate discrepancies, and establish a maintainable data foundation.
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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.

  • The ability to investigate discrepancies, understand their root causes, and make the underlying systems more reliable.

  • Strong ownership: you can identify what needs to happen, prioritize it, and carry it through without detailed instructions.

We expect this experience will often come from around six or more years of relevant work, but the depth of your ownership and what you’ve built matter more than a specific number.

Bonus Points For:
  • Building data foundations at a startup or on a small team.

  • Supporting Finance, Revenue Operations, Growth, or GTM.

  • Working with usage-based products, billing data, or cloud infrastructure costs.

  • Building well-documented datasets that support self-service analytics and AI tools.

Finance domain expertise is helpful, but it isn’t required. We’re looking for an engineer who is curious about the business, learns quickly, and takes responsibility for delivering data people can trust.

What it’s like to work at E2B

We’re a fast-growing startup with in-person (4 days on-site, 1 day WFH) offices in San Francisco and Prague, Czech Republic. We already generate 8-figure revenue and work directly with top-tier AI companies like Manus, Genspark, Lindy, Groq, Artificial Analysis and other exciting teams pushing the frontier of AI.

We offer healthcare, vision, and dental insurance, unlimited PTO, 401k, and a variety of perks for in-office employees.

HQ

E2B San Francisco, California, USA Office

San Francisco, CA, United States

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