Systems — Operational Software, Data & Recovery

40%

lower reporting latency

Operational reporting pipeline

Redesigned the reporting layer and production data pipelines behind operational Power BI and SSRS reporting in a live mining environment.

15%

reduction in equipment idle time

Python and SQL automation that made equipment information move faster and more consistently through operational reporting and follow-up.

<1h

recovery path, down from four hours

Rebuilt and exercised the recovery procedures for systems that support continuous mine operations.

40%lower reporting latency

Context: Operational Power BI and SSRS reporting inside a live mining environment.
Baseline: The previous reporting path took longer to move production information into decision-ready reports.
Intervention: Redesigned the reporting layer and its production data pipelines.
My role: Data-system design, implementation, and operational support.
Verification: Observed against the previous production reporting path. Internal records and absolute timings are confidential.

15%reduction in equipment idle time

Context: Equipment information moving through operational reporting and follow-up workflows.
Baseline: Manual and delayed information flows slowed action around idle equipment.
Intervention: Introduced Python and SQL automation to improve information speed and consistency.
My role: Automation design, data engineering, and delivery.
Verification: Reported operational outcome from the improved workflow. Measurement records and attribution detail are not public.

<1hrecovery path, down from four hours

Context: Disaster recovery for systems supporting continuous mine operations.
Baseline: The documented recovery path was approximately four hours.
Intervention: Rebuilt and exercised recovery procedures around operational continuity.
My role: Recovery-path design, procedure implementation, and validation.
Verification: Documented and exercised recovery path. Infrastructure detail is withheld for security.

5+ yrsinside production operations

Context: A 24/7 industrial environment where software and data failures affect physical work.
Baseline: Experience spans production IT, data engineering, automation, reporting, and recovery.
Intervention: Continuous delivery and support across operational systems rather than a single project.
My role: Systems engineer, software developer, data engineer, and automation builder.
Verification: Professional operating context; sensitive employer systems and records remain private.