Selected Engineering Problems¶

These examples focus on the constraints, decisions, and outcomes behind my work. Internal project names and some organizational details have been omitted.

Authorization at the platform boundary¶

An enterprise data-access platform needed to let users query multiple systems without provisioning each user into every upstream source. The earlier service-account-per-integration approach did not provide the user-level governance the platform required.

I designed the platform to hold upstream credentials while evaluating each user's access through platform-managed roles and grants using OpenFGA. This made authorization, identity provisioning, and auditing central parts of the design. The control plane managed users, groups, and access assignments, with auditing of both administrative changes and data-access events.

Multi-tenancy and deployment in isolated environments were requirements from the start, so the design could support different identity providers and operating environments.

Public access with strict request validation¶

Customers needed to manage communication preferences without signing in, including through links in email. The service had to accept traffic from a broader range of clients than existing integrations supported, while protecting against malformed requests and excessive traffic.

The original design relied on an API gateway for rate limiting and payload verification. When that infrastructure was no longer available, I split those responsibilities between the edge layer and the application. Rate limiting had to account for legitimate clients sharing egress addresses. Application middleware enforced JSON schemas for each payload variant and validated email addresses before accepting requests.

The JSON-schema validation pattern was subsequently adopted by more than five other services.

Coordinating incident response across team boundaries¶

During an on-call rotation, I traced a spike in failed authentication requests to a service owned by another team. I opened an incident with the security operations team and coordinated investigation and mitigations with the service and edge-infrastructure owners.

While a longer-term fix was being developed, I built monitoring that aggregated failed logins by traffic source and client characteristics. It identified further attacks during the remediation period and gave the responding teams a shared view of suspicious activity. My contribution was detection and response coordination; I do not attribute a measured reduction in account compromises to that monitoring.

Keeping a partial cloud migration operable¶

A cloud migration moved application services before their databases, and the program's scope changed while that split architecture was already in use. Services needed to remain operable across both environments without assuming that the migration would finish on its original schedule.

I built a service inventory, container-image and CI tooling, secured cross-cloud proxies, and procedures for performance-testing services whose databases remained in the other cloud. These gave teams a practical way to deploy, operate, and troubleshoot the intermediate state.

When the program was curtailed, the tooling, services, and operating procedures remained useful.

Reliable data pipelines under infrastructure constraints¶

A CRM-to-warehouse synchronization process relied on legacy ETL jobs that frequently timed out and paged the on-call engineer. Replacement infrastructure was constrained by budget and scheduling capabilities, and the new tools needed to operate with little ongoing maintenance.

I used an existing warehouse adoption effort to establish schemas owned by my team and collaborated with the platform-automation team to secure access to batch execution infrastructure. I then designed the replacement around recoverability: restartable runs, pre-flight checks on source APIs and target structures, per-run staging tables, and provisioning of new target objects. Staging handled irregular source text that could break direct CSV loads.

Jobs ran on ephemeral compute that shut down after execution. Local simulation supported development without a complete local replica of the source system. A later version replaced full-file downloads on large instances with chunked processing and progress tracking on smaller instances.

The framework processed roughly 300 GB nightly. Large objects that previously ran past the next scheduled load completed in hours, and pages fell from nightly to a couple per month, then further after retry improvements. The system remained in production years after handoff.

Shared terminology with conflicting meanings¶

Improving generated-query accuracy for one business group degraded it for another. Both groups used the same business terms, but their definitions represented different relationships and workflows.

I worked with subject-matter experts to separate the vocabularies and govern them per consumer group. This became a reusable pattern in the data-access platform: each team owns its taxonomy and definitions, and queries use the appropriate context instead of forcing a single shared interpretation.

Reusable review of sensitive warehouse data¶

A dataset-onboarding request exposed the need for a repeatable way to identify fields requiring security review before use in AI workflows. I built a classification and review process with the security architecture team.

The scanner used metadata, including table names, column names, and column statistics, to prioritize fields for review. A review interface provided a validation query for each flagged field. Decisions persisted in a database that also served as an audit record.

The data-access platform consulted that record during onboarding to distinguish previously reviewed datasets from those needing review. This reduced repeated review work across requests; metadata scoring supported triage rather than serving as proof that a dataset contained no sensitive information.