Case Studies

Founded a new reporting service that separates heavy analytical reads from the transactional database, resolving indicator timeouts, framing the OLTP-vs-OLAP trade-off, critically reviewing the architecture decision, and building the walking skeleton and its data layer.

Root-caused a customer-blocking production incident to an undocumented architecture assumption, rebuilt the affected consumer with a post-mortem, an ADR, and business-rules documentation, then, after rollout exposed a database deadlock, diagnosed it to a Kafka partitioning mismatch and replaced silent message loss with retry, a dead-letter queue, and per-user serialization.

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.

Delivered search and fast navigation over very large asset trees end to end, with recursive SQL on the backend and a search UX with in-memory caching and progressive background prefetch on the frontend, eliminating the repeated loading that made the most-used flow slow.

Designed and built a Claude Code skill that safely orchestrates parallel agents to remove expired feature flags across a shared frontend and two backend services, closing a 36-subtask cleanup epic (24 feature flags plus 3 expired product tours and a legacy page, ~3,100 lines removed in one commit), with disjoint-file-set batching so agents can't collide, diff-against-baseline validation instead of absolute pass/fail, and an enforced two-repository deploy order so infrastructure changes can never precede the code that depends on them.

Turned a non-deterministic end-to-end suite (25 to 37 failures varying per run) into 302 passing with zero failures (8 pre-existing skips left untouched, and the consumer running), without adding a skip or weakening an assertion, and, in review, empirically proved that three of four proposed production changes were unnecessary.

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.

A new platform-wide asset state was specified as a rule that eight different read paths had to learn. I proposed applying it once at the write boundary instead, removing the asset from route scope and restoring it on reactivation, which made most of the original scope unnecessary and left the counters, reports, app sync and adherence untouched.

Gave a team that had no error monitoring a structured observability practice built from a shared reporter and request-time-tagged API interceptor plus dashboards and a triage workflow, turning production bugs from something reported by support into something the team can see and prioritize.

In code review, caught a null-safety bug that would have crashed three production components, and fixed the defect class rather than the three instances, by proposing a shared data-layer helper to the PR's author instead of patching each render site myself; one of 310 pull requests I gave an explicit review verdict on that half (702 across four repositories between 2025-03 and 2026-08), measured from the Bitbucket API rather than recalled.