Bioinformatics Data Engineer

Love taking raw scientific data and turning it into something researchers can trust and use? Come work with a team shaping lab, research, and genomics data for life sciences startups, CROs, and instrument developers doing work that matters.

We help scientific organizations solve hard problems and move their industries forward, from life sciences startups and CROs to the teams building lab software and scientific instruments. It's work we're proud of, and we're excited about the successes still ahead.

Join a team recognized as one of Madison Magazine's Best Places to Work, where innovation thrives and collaboration drives success. We don't just build software. We empower people and transform industries.

• This is a hybrid position based out of our office in Madison, WI.
• We are unable to provide sponsorship.

You’ll work on client projects where the data is the hard part: messy, high-volume, and scientifically complex. You’ll clean it, structure it, and analyze it so scientists get answers faster. You’ll set technical direction, grow the engineers around you, and be the person clients call when their data isn’t telling them anything yet.

We build on strong engineering fundamentals: solid methodology, rigorous testing, and sound architecture. We use AI tools like Claude and Codex where they speed up delivery, while keeping critical thinking and engineering discipline at the center. We own the quality, accuracy, and understanding of the code we ship.

• Turn raw lab, research, and genomics data into clean, analysis-ready datasets.
• Design data models that make scientific data easy to query and reuse.
• Build repeatable pipelines so analysis doesn’t start from scratch every time.
• Apply statistical methods and exploratory analysis to find what the data is saying.
• Create visualizations that help researchers see results at a glance.
• Build data quality checks that catch problems before they reach a result.
• Partner with scientists to understand the biology behind the data.
• Own technical delivery for your project team: quality, pace, and direction.
• Mentor the engineers on your team through code reviews and one-on-one problem solving.
• Help engineers work through hard problems instead of solving them for them.
• Present results, tradeoffs, and risks to clients in plain language.
• Join pre-sales conversations with solution outlines and rough estimates.
• Document key decisions in ADRs so the next team knows why, not just what.

• 6+ years in data science, data engineering, or software engineering.
• Hands-on experience wrangling large, messy datasets into usable form.
• A working knowledge of statistics and exploratory data analysis.
• Time leading technical work for a team, formally or informally.

• Real curiosity about the science behind the data.
• Rigor about data quality, reproducibility, and traceability.
• Genuine interest in helping other engineers grow.
• Ability to explain findings to scientists and non-technical stakeholders alike.

• Experience with lab, research, genomics, or bioinformatics data.
• Familiarity with LIMS, ELNs, or instrument data.
• Work in regulated environments (HIPAA, FDA, GxP, 21 CFR Part 11).
• Machine learning applied to scientific data.
• Consulting or client-facing project experience.

• Python (pandas, Num Py, Sci Py) and/or R
• Notebooks like Jupyter
• Workflow tools like Nextflow, Snakemake, and Airflow
• Relational and analytical databases (Postgres, SQL Server, Databricks, or similar)
• Visualization tools like Plotly, ggplot2, or Power BI
• Cloud platforms:
  Microsoft Azure and Amazon Web Services