Lab Data Platform Engineer

Arc Institute; Palo Alto (CA); On-site; USD 118,000 - 146,000; Full time

Job summary

Arc Institute in Palo Alto is seeking an Infrastructure Engineer to own support and operations for our laboratory information management system (LIMS). You will help scientists record experiments, manage data schemas, and automate repetitive tasks, with mentorship from a Tech Lead.

You’ll apply strong Python and SQL skills, work with REST APIs, and help build tools that improve data quality and analysis across the lab environment.

Qualifications

• Bachelor’s degree with 0-2 years of relevant experience, or an advanced degree.
• Solid Python and SQL, comfortable working with REST APIs.
• Debug problems in systems you didn’t build, using code, logs and data.
• You use AI coding tools day to day or are ready to learn, and you’re careful with sensitive research data.
• Explain technical things clearly to scientists, and you write docs and training that people use.
• Work onsite in our Palo Alto office at least 3 days a week.

Responsibilities

• Run the request queue for Arc's lab data systems, shipping changes through the change workflow.
• Support templates scientists record experiments with, and the command-line tools that pull data for analysis.
• Run training sessions for scientists, and write the docs they come back to.
• Build and maintain checks that catch errors in data as scientists enter it.
• Help carry out the refactor of the team and permission structure in our LIMS.

Skills

Python

SQL

REST APIs

AI coding tools

Technical writing

Education

Bachelor’s degree

Advanced degree

Tools

Benchling

CI pipelines

Job description

Arc Institute in Palo Alto is seeking an Infrastructure Engineer to own support and operations for our laboratory information management system (LIMS). You will help scientists record experiments, manage data schemas, and automate repetitive tasks, with mentorship from a Tech Lead.

You’ll apply strong Python and SQL skills, work with REST APIs, and help build tools that improve data quality and analysis across the lab environment.