Receive
Events arrive through REST services, JSON/XML payloads, or scheduled SFTP exchanges.
API & SYSTEMS WORK
I make complex systems
easier to trust.
My API experience comes from enterprise implementation: tracing data across systems, validating payloads and databases, isolating failures, automating repeatable checks, and helping teams reach launch readiness. The examples below are sanitized to protect customer and employer data.
RESTEndpoint and integration validation
JSON / XMLPayload inspection and schema troubleshooting
SFTPFile-based data workflows and monitoring
SQL / NoSQLPostgreSQL and MongoDB investigation
SANITIZED ENTERPRISE PATTERN
From incoming event to trusted operational state.
Validate
Confirm schemas, required fields, identifiers, timestamps, and the expected system state.
Trace
Follow the event through services, logs, PostgreSQL or MongoDB, and connected platforms.
Resolve
Translate findings into a defect, configuration change, automated check, or clear team action.
Prove
Retest the path, exercise edge cases, document evidence, and prepare users for launch.
PAYLOAD WALKTHROUGH
What I look for before calling an integration “working.”
A 200 response is not enough. I check whether the right event arrived, the identifiers match across systems, the state changed as expected, and the evidence is visible to the teams responsible for support.
These payloads are illustrative—not employer source code or customer data.
REQUEST
POST /api/v1/outages/validate{
"eventId": "OUT-4821",
"source": "SCADA",
"status": "OPEN",
"devicesAffected": 14,
"observedAt": "2026-09-29T14:22:08Z"
}RESPONSE
202 Accepted{
"accepted": true,
"workflow": "OMS_IMPORT",
"validation": {
"schema": "passed",
"crossSystemId": "matched",
"duplicate": false
}
}EVIDENCE
The work behind the keywords.
Cross-system implementation
Supported integration and launch work spanning OMS, DMS, SCADA, SOM, CMS, GMS, Salesforce, and adjacent utility systems.
- 800K–1M customer service territory
- 50K–75K simulated outage scenarios
- Requirements through user enablement
Repeatable investigation
Used Python and PowerShell to support monitoring, SFTP workflows, log analysis, data checks, and technical readiness.
- Linux and Windows environments
- PostgreSQL and MongoDB troubleshooting
- Defect evidence and retesting
DayKind architecture
DayKind is currently a local-first planning prototype. I am validating the problem before claiming a public API or production backend.
- Product requirements and user flows
- Local-first data model
- API boundary planned after validation
FOR TECHNICAL REVIEWERS
Ask me to walk through a failure.
The most useful discussion is not a list of tools. It is how I narrowed a cross-system problem, proved where it failed, communicated the result, and helped the team move forward.
Request a technical walkthrough