Reliability

A per-request warehouse join was scanning 658.8 MB against a hard 953.7 MiB per-job ceiling, on a table growing with every new customer. I measured it, moved the join into the pipeline that already ran it, deleted the cache that was hiding the problem, then audited my own migration and found 79% of production rows never backfilled, plus 9,299 alerts that had never appeared in the product at all.

Corrected tens of thousands of corrupted production records (~33k in one case) with no maintenance window, using reusable CLI commands with dry-run, rollback files, batch auditing and event re-publishing, a "correction command" pattern the team then reused.

Turned container and dependency hardening into a standing quarterly practice across two backend services over four quarters, covering non-root runtimes, 135 CVEs flagged and all 7 rated critical remediated in the first pass, then a base-image and dependency overhaul that took the audit from 69 findings to 16, unfixable OS CVEs from 160 to 0, and the final image from 1.64 GB to 463 MB, with exploitability-based accepted risk documented rather than version numbers chased, and one self-inflicted rollout regression root-caused and fixed the same day.

Made an edit to an organizational node in the asset hierarchy propagate consistently across denormalized copies in seven tables and two services, via a single atomic transaction with post-commit events, the work that made me the team's reference for cross-service synchronization.