---
title: 'Data Engineer at Benchling'
canonical: 'https://feeny.ai/job/data-engineer-benchling-san-francisco-t66wxxppap76'
type: 'job'
last_seen: '2026-09-10'
---

# Data Engineer at Benchling

- **Company:** Benchling
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-08-28
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.ashbyhq.com/benchling/c1ad7288-ad78-4a0f-8f19-1fcc3f6cf85b

## Job description

We are rebuilding biotech for the AI era.

When a breakthrough is delayed, the world waits. Getting a molecule from discovery to patients, or a crop from lab to field, involves thousands of slow, manual, disconnected steps. AI has the potential to change this, compressing decades of R&D work into years. But that only happens when clean, structured scientific data and AI are built into how science gets done.

Benchling is the AI platform for biotech R&D. Scientists use Benchling to design experiments, capture structured data, and run AI agents and models directly in their workflows. Over 200,000 scientists around the world trust Benchling to power their most important work, from academic labs to Sanofi, Moderna, and more than half of the world's top 50 biopharma.

We’re building an AI scientist for our customers. We can’t do that if we haven’t built the muscle ourselves. AI fluency is the foundation we build on; it's core to how we work, and we're committed to helping every new hire integrate it into their day-to-day. As part of our interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today.

## ROLE OVERVIEW

Biotechnology is rewriting life as we know it, from the medicines we take, to the crops we grow, the materials we wear, and the household goods that we rely on every day. But moving at the new speed of science requires better technology. Benchling's mission is to unlock the power of biotechnology. The world's most innovative biotech companies use Benchling's R&D Cloud to power the development of breakthrough products and accelerate time to milestone and market. Come help us bring modern software to modern science. Benchling is building AI & Data Engineering (AIDE), a small, autonomous team within our Security & IT organization. AIDE owns three things: internal AI tooling, adoption, and AI-assisted workflows across the company; cross-functional and company-wide agentic AI applications that no single department owns; and the enterprise data engineering, analytics architecture, and source-of-truth datasets that everything above depends on. AIDE’s data and analytics functions grew out of our former Data, Analytics & Systems (DAS) team, and this role carries forward DAS's original charter: building and running the data pipelines, warehouse, and analytics infrastructure that the entire company relies on for trustworthy answers. This is a data engineering role — we want someone who builds and operates reliable, production-grade data pipelines and warehouse infrastructure, not a data scientist focused on modeling or analysis. This role exists because AIDE's data function supports the whole company — GTM, Customer Success, Product, Finance, and beyond — not just one team, and the team needs to grow to support these initiatives as we expand the team’s scope and portfolio. You'll own core pipelines end to end (ingestion, transformation, warehouse, and the BI/analytics layer on top), partner with the rest of the data team on the team's data architecture, and help build the trusted data foundation that AIDE's AI-adoption and agentic AI work increasingly depends on. Check out our engineering blog for examples of past work across Benchling.

## RESPONSIBILITIES

- Own core data pipelines end to end: Build and operate the ELT pipeline that moves data from Benchling's product, Salesforce, and third-party systems into Snowflake, modeled with dbt, and built to production standards — testing, monitoring, schema versioning — that hold up as usage scales. This is infrastructure the rest of the company builds on, not a one-off project.
- Build the data foundation for AIDE's AI initiatives: Partner with AIDE's AI engineering side to make governed, trustworthy data available for the agentic AI tooling and internal AI applications the team ships.
- Own data governance and pipeline health: Maintain Snowflake access controls (RBAC), monitor data quality, uphold PII-handling and data-access policy, and manage warehouse cost and performance as usage grows.
- Contribute to platform strategy: Weigh in on bigger structural decisions — warehouse architecture, semantic layer/metrics store design— alongside the rest of the data and AI engineering team.

## QUALIFICATIONS

- 3+ years of professional experience building and operating production data pipelines — ingestion, transformation, and modeling data into a cloud data warehouse.
- Strong SQL and Python skills; hands on experience with data modeling methodologies and tools, preferable with dbt.
- Experience applying software engineering practices to data systems — version control, code review, CI/CD, automated testing — and comfort working with cloud infrastructure (AWS or similar) supporting production pipelines.
- Experience with Snowflake or a comparable modern cloud data warehouse in production.
- Comfort with orchestration tooling (Airflow or similar) for scheduled data jobs.
- Track record supporting many stakeholders across departments such as Sales, CS, Product, Finance, rather than a single internal customer.
- Understanding of data privacy, governance, quality, and testing frameworks and best practices.
- Strong communication skills; comfortable translating ambiguous requests from non-technical stakeholders into a scoped, buildable data solution.
- Comfortable in a small, fast-moving, still-forming team — AIDE only stood up in its current form in mid-2026 and is actively defining its own processes.
- Interest in learning more about life science (prior knowledge is not required).

## NICE TO HAVE

- Familiarity with product behavioral data and a modern BI tool (Sigma, Omni, Looker, Tableau) deployed in a self-service model.
- Experience with product/usage analytics instrumentation and event-taxonomy governance.
- Familiarity with GTM analytics tools such as Salesforce.
- Exposure to AI-usage telemetry, LLM observability data, or supporting AI/ML tooling with curated data.
- Background in enterprise SaaS, life sciences, or biotech.
- Experience building or maintaining a metrics layer.

## HOW WE WORK

We offer a flexible hybrid work arrangement that prioritizes in-office collaboration. Employees are expected to be on-site 3 days per week (Monday, Tuesday, and Thursday). #LI-Hybrid #BI-Hybrid

## #LI-CG1

Benchling welcomes everyone. We believe diversity enriches our team so we hire people with a wide range of identities, backgrounds, and experiences.

We are an equal opportunity employer. That means we don’t discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We also consider for employment qualified applicants with arrest and conviction records, consistent with applicable federal, state and local law, including but not limited to the San Francisco Fair Chance Ordinance.

## About Benchling

## Company Overview
- **One-liner**: Benchling provides a cloud-based platform for biotechnology research and development, uniting data, automation, and AI to accelerate scientific discovery.
- **Entity Type**: Private (Series F)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2012
- **Founders**: Sajith Wickramasekara, Ashu Singhal

## Core Business
- **Primary industry/industries**: Life Sciences Software, Biotechnology R&D, Scientific Cloud Computing
- **Target customers**: B2B; biopharma companies (including more than half of the world's top 50), academic labs, agritech, and industrial biotech organizations.
- **Mission or purpose statement**: "To unlock the power of biotechnology" by helping scientists unite data, automation, and AI to bring new products and discoveries to life faster.

## Products & Services
- **Benchling Platform (R&D Cloud)**: A unified, cloud-based platform for biotech R&D. It includes an electronic lab notebook (ELN), laboratory information management system (LIMS), and scientific data management. It allows teams to plan, record, and share experiments, automate workflows, and use AI tools.
- **Benchling AI**: An integrated AI layer that includes "The AI Scientist," which connects predictive models, structured data, and wet lab execution into a single loop. It designs experiments, routes lab automation, captures results, and recommends next steps.
- **Developer Platform**: An open, flexible platform with APIs, app integrations, and a custom interface designer, allowing organizations to build custom apps and connect data from instruments and other software.
- **Services & Support**: Implementation, advisory, and support services from a team of experts. Also offers "Benchling Learning Labs" for team training and certification.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed (last reported valuation was $6.1 billion in 2021 after a Series F round).
- **Key Metric**: Total funding of **$412M** across 8 rounds. Annual revenue is estimated at **$50M** (per LinkedIn).
- **Notable Investors/Partners**: Menlo Ventures, Sequoia Capital, Accel, Y Combinator, and others. Customers include Sanofi, Moderna, and more than half of the world's top 50 biopharma companies.
- **Growth Signals**: Over 200,000 scientists use the platform; trusted by 1,300+ organizations; 642 employees with 2.2% YoY headcount growth; active job postings (49 open roles); LinkedIn follower growth of 28.4% year-over-year.

## Competitive Advantages
- **Purpose-built for biology**: Unlike generic software, Benchling is built specifically for complex life sciences R&D, modeling data for biomolecules, cell lines, and more.
- **AI-native platform**: AI is embedded at every step, with "The AI Scientist" closing the loop between experiment design, execution, and data capture.
- **Network effects**: Over 200,000 scientists and 1,300+ organizations use the platform, creating a strong ecosystem and data network effect.
- **Deep industry penetration**: Trusted by more than half of the world's top 50 biopharma companies, providing a strong moat against competitors.
- **Open and flexible**: Offers APIs, integrations, and a custom interface designer, allowing it to adapt to diverse scientific workflows.

## Strategic Focus
- **AI-first R&D**: Deeply integrating AI agents and models into the scientific workflow to compress decades of R&D into years.
- **Platform expansion**: Continuing to build out the "AI Scientist" capability and expanding the developer platform for custom applications.
- **Customer growth**: Deepening relationships with existing enterprise customers (top 50 biopharma) while expanding into adjacent fields like agritech and industrial biotech.
- **International presence**: Operating in 15 countries, including Switzerland, UK, France, Denmark, and Canada, with continued global expansion.

## Why Work Here
- **Mission-driven work**: Employees directly contribute to accelerating breakthroughs in medicine, agriculture, and materials science.
- **Culture of curiosity**: The company emphasizes a growth mindset, continuous learning, and treating mistakes as opportunities to reflect and grow.
- **Strong benefits**: Includes dedicated mental health benefits (therapy sessions), monthly wellness stipend, winter holiday shutdown, and active employee resource groups (ERGs) with executive sponsorship.
- **Community and connection**: Regular social hours, themed all-hands meetings, cross-functional events, and a strong emphasis on building community both in-person and virtually.
- **Hybrid/Office policy**: Has offices in multiple locations (San Francisco, and international offices in Switzerland, UK, France, Denmark, Canada) with in-person social hours and team events.
- **Engineering culture**: Nearly half the team comes from an R&D background, blending scientific and technological expertise. Open roles include Software Engineer (Agents, Developer Platform), Engineering Leader (Molecular Biology, Infrastructure), and more.

## Sources
1. [benchling.com](https://www.benchling.com/)
2. [benchling.com/about-us](https://www.benchling.com/about-us)
3. [benchling.com/careers](https://www.benchling.com/careers)
4. [benchling.com/life-at-benchling](https://www.benchling.com/life-at-benchling)
5. [linkedin.com/company/benchling](https://www.linkedin.com/company/benchling)

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