Spend the semester at Floodlight turning raw space age data into climate insight. You will spend 10 to 20 hours each week between coursework and code, ship features that touch production, and leave with a clear story of impact.
What you will work on
• Extend our alerting pipeline so risk events and anomalies reach Slack and email with helpful context, not noise.
• Add layers and interactions to our React geospatial dashboard. Think facility matching, polygon joins, and asset level risk views.
• Keep Google Cloud spend honest by profiling jobs, tuning BigQuery, and simplifying data paths.
• Demo wins every sprint to the exec team and write short notes that explain the why, not just the what.
Example projects you could own
• A nightly CO2 plus activity data stitch that reconciles facility IDs across EPA, EIA, and our internal registry, complete with data quality checks.
• An alert rule that fuses NASA wildfire detections and local weather to flag likely emission spikes for targeted follow up.
• A tiny evaluator that compares suggested mitigations against historical results to rank actions by expected impact and effort.
What you will learn
Modern data engineering on Google Cloud. Practical geospatial with Python, SQL, and React. Alert design that users actually keep on. Shipping code with code review, tests, and on call empathy. Telling a product story with data.
Our stack
Python, SQL, Node, React, Git, Docker, Google Cloud with Pub Sub, Cloud Functions, Cloud Run, and BigQuery. GeoPandas and PostGIS show up often. If you have not touched one of these yet, we can teach it.
You are a good fit if
• You can read an API doc and get a working client without drama.
• You are comfortable with Python and SQL. React experience is a plus.
• You like turning messy datasets into decisions.
• You communicate clearly and keep promises small and on time.
Time and location
September to December. Twelve to twenty hours per week. Remote friendly with at least three hours of overlap in Central Time. Austin or Vienna meetups happen sometimes.
Compensation
Paid internship.
Deliverables you will finish
• One production data job with tests and monitoring by week six.
• One shipped feature or analyst tool by the end of term.
• A short write up that explains impact, tradeoffs, and next steps.
How to apply
Send a resume, a paragraph about a project you loved, and links to GitHub or a brief code sample. If you have a map or data viz you are proud of, include a screenshot.
Please contact us to apply.
