Data Engineer

Verasight is hiring a Data Engineer to build and maintain the tools and data infrastructure behind its survey research. The role works closely with data scientists to improve workflows, automate processes, and help guide the company’s data infrastructure.

Responsibilities:

• Build and maintain internal tools, packages, and pipelines (largely R and Python) that remove bottlenecks from survey fielding, data cleaning, weighting, reporting, and panel monitoring
• Work alongside data scientists on live projects to learn their workflows before automating them, so the tools fit how people actually work
• Respond quickly when a data scientist hits a wall; you'll often be the first call
• Scope problems well: decide whether a need calls for a script, a package, a scheduled job, a service, or nothing at all
• Use AI coding and analysis tools as a real part of your workflow, verify what they produce, and help shape what responsible AI use looks like at Verasight
• Partner with Verasight leadership on where our data infrastructure should go, solving today's problems in ways that help us move into the future

Requirements:

• 2+ years writing code that other people depend on, in Python or R, and willingness to work in the other
• Comfort with SQL and relational databases
• Working fluency with Git, GitHub, and code review
• Some experience with cloud services or managed platforms (we use AWS, Supabase, Railway, and Vercel, among others); we care more that you can learn a platform and less about the specific stack you're most comfortable with today
• Sound security instincts: you keep secrets out of code, think about who can access what, and handle sensitive data carefully
• Hands-on experience using AI tools to write or review code, and informed opinions about where they help and where they don't
• Excellent written communication, including clear READMEs and short design notes
• Willingness to operate independently and desire to constantly innovate
• Commitment to working in an inclusive environment
• experience with survey data or Qualtrics
• R package development
• CI/CD (GitHub Actions)
• containers or infrastructure-as-code
• scheduled data pipelines
• familiarity with survey methodology (weighting, sampling, data quality checks)