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. ROLE OVERVIEW At Benchling, we’re tackling some of the most complex problems in life sciences R&D—and that takes engineers who thrive on solving high-impact, systems-level challenges. As a Data Platform engineer, you’ll build the next generation of infrastructure that powers real-time scientific discovery. You’ll architect multi-tenant pipelines, develop change data capture (CDC) systems, and design scalable, privacy-aware solutions that enable our customers—scientists and researchers—to move faster and smarter. This is a rare opportunity to do deep engineering work with a clear line of sight to real-world health outcomes . “There’s a lot of software where you don’t know if it helps the world. Here, the mission and the moment are aligned—you know your work matters.” Whether you’re building tools that help accelerate vaccine development or scaling infrastructure for biotech R&D, your work here matters. RESPONSIBILITIES Own core systems end-to-end—from design and prototyping to deployment and scale. Build real-time data infrastructure (CDC pipelines, search indexing and more) that powers customer analytics and platform extensibility. Design CI/CD workflows and internal tooling that make our platform easy to operate, secure, and maintain. Collaborate with product managers, platform architects, and internal developers to define a shared vision for data at Benchling. Set standards for data integrity, privacy, and reliability across internal and customer-facing systems. Champion platform engineering best practices and influence how Benchling teams interact with data at scale. QUALIFICATIONS You bring 10+ years of engineering experience , including 5+ years with distributed data processing frameworks (e.g., Kafka, Debezium, Spark, Flink). You’re hands-on with infrastructure tooling like Kubernetes, Terraform, or ECS , and scripting in Python or similar. You value clean abstractions and solving root problems—not just shipping workarounds. You’re a clear communicator, both in code and in writing, and bring a collaborative spirit to technical planning. You may not have a background in biology —and that’s okay. Many of our best engineers come from FinTech, infrastructure, or consumer tech. What matters most is curiosity and a willingness to learn . You want to build for deeply technical users —scientists with PhDs doing life-changing work. You value autonomy, iterate instead of over-planning , and seek impact over optics.
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