数据工程师
Data Engineer
我们正在为人工智能时代重建生物科技。
当突破被延迟时，世界就会等待。将一种分子从发现到患者，或一种作物从实验室到田间，需要数千个缓慢、手动、不连贯的步骤。人工智能有潜力改变这一切，将数十年的研发工作压缩成几年。但只有当干净、结构化的科学数据和人工智能被融入科学研究的过程中，这种改变才会发生。
Benchling 是生物技术研究与开发的人工智能平台。科学家使用 Benchling 设计实验、捕获结构化数据，并在他们的工作流程中直接运行 AI 代理和模型。全球超过 20 万名科学家信任 Benchling 来推动他们最重要的工作，从学术实验室到 Sanofi、Moderna，以及全球前 50 强生物制药公司中的超过一半。
我们正在为客户打造一位 AI 科学家。如果我们自己没有建立起相应的实力，就无法做到这一点。AI 熟练度是我们构建的基础；它是我们工作方式的核心，我们致力于帮助每一位新员工将其融入日常工作中。作为我们面试流程的一部分，你将完成一个简短的 AI 相关练习或讨论，以便我们了解你如何思考并利用 AI 在你的角色中产生影响。欢迎参考你目前使用的任何工具、平台或工作流程。
职位概述
生物科技正在重新定义我们所知的生命，从我们服用的药物，到我们种植的作物，我们穿着的材料，以及我们每天依赖的日用品。但以新的科学速度前进需要更好的技术。Benchling 的使命是释放生物科技的力量。世界上最创新的生物科技公司使用 Benchling 的 R&D Cloud 来推动突破性产品的开发，并加速里程碑和市场到达时间。来帮助我们将现代软件带入现代科学吧。
Benchling 正在构建 AI 与数据工程（AIDE），这是我们的安全与 IT 组织内部的一个小型、自主团队。AIDE 负责三件事：公司在内部的 AI 工具、采用情况以及 AI 协助的工作流程；跨职能和全公司范围的代理型 AI 应用，这些应用没有单一部门拥有；以及所有上述内容所依赖的企业级数据工程、分析架构和真实数据集。AIDE 的数据和分析功能源自我们之前的“数据、分析与系统”（DAS）团队，这个职位延续了 DAS 最初的使命：构建和运行数据管道、仓库和分析基础设施，整个组织都依赖于此。
查看英文原文
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.