Juan David Trejos Gamboa

● Maintained 99.9% data accuracy across high-volume, real-time datasets, as measured by internal quality benchmarks, by validating and monitoring incoming structured data feeds. ● Reduced data inconsistencies and reporting errors, as measured by incident-tracking metrics, by investigating anomalies, determining root causes, and documenting corrective actions across multiple data sources. ● Increased issue-resolution speed, as measured by escalation response time, by documenting repeatable data workflows and procedures for distributed operational teams. ● Improved operational decision-making support, as measured by downstream reporting accuracy, by monitoring performance metrics and communicating findings clearly to stakeholders.

● Owned end-to-end payroll and retirement operations for a portfolio of 90+ clients, as measured by on-time, accurate payroll delivery, achieving 100% data accuracy through reconciliation audits. ● Reduced manual operational workload by 15+ hours per week, as measured by workflow tracking, by building automation with Python scripting alongside modern AI-driven tools — including Claude Code, Cursor, n8n workflow automation, and MCP (Model Context Protocol) integrations. ● Reduced data discrepancies by 20%, as measured by synchronization error rates, by writing SQL queries to clean, normalize, and cross- validate data across relational systems. ● Improved team operational visibility and efficiency, as measured by task completion tracking, by implementing an Agile workflow with dashboards, tasks, and subtasks in Jira, supported by daily standups. ● Drove operational decision-making, as measured by KPI tracking presented in daily standups, by developing SQL queries on PostgreSQL (via Mode) to monitor team performance and surface improvement opportunities. ● Improved reporting reliability, as measured by a reduction in validation failures, by implementing automated data quality monitoring and anomaly detection.