Internal applications: Build and maintain the internal web applications engineers use to work with flight data — flight record browsers, query interfaces, and analysis tools over the warehouse. 

Backend services: Develop Python services and HTTP APIs that query Athena and S3 and return results at interactive speed, including pagination and caching over large result sets. 

Front end: Build interfaces that make large telemetry datasets explorable — sortable tables, filters, and time-series plots — for engineers who are never going to write SQL. 

AI-assisted diagnosis: Build agent-based tooling over the data platform so engineers can ask questions in plain language and follow a symptom through to a root cause without hand-writing queries. Design these tools to return the underlying data and how it was derived, not just an answer, so an engineer can verify the result before acting on it. 

Self-serve analysis: Turn recurring one-off analyses from the firmware, GNC, battery, and maintenance teams into supported, self-serve tools instead of scripts that only their author can run. 

Data catalog: Generate the internal field guide and data catalog from the warehouse itself, so what engineers read cannot drift from what the tables actually contain — and keep that metadata machine-readable, so the tooling and agents built on top of it interpret results correctly. 

Alert review: Build the review and triage surfaces for fleet health alerts — acknowledgment, history, and trend views — alongside the existing dashboards and Slack notifications. 

Tooling distribution: Package and distribute analysis tooling so it runs on an engineer's laptop, Windows included, without someone walking them through an environment setup. 

Ownership: Carry your work through deployment — tests, code review, CI/CD, and the monitoring that tells you when something breaks. 

Collaboration: Sit with the engineering teams to scope what they actually need, and document what you ship so the next person can support it.