نبذة عني
Senior Data Analyst and Business Intelligence Engineer with 3+ years of enterprise experience delivering end-to-end BI, SQL performance engineering, ETL development, and executive reporting in the US Mortgage industry. I…
Senior Data Analyst and Business Intelligence Engineer with 3+ years of enterprise experience delivering end-to-end BI, SQL performance engineering, ETL development, and executive reporting in the US Mortgage industry. Independently owned full project lifecycles — requirements gathering, data architecture, Power BI dashboard development, SSRS report engineering, UAT coordination, and production deployment. Recognized by VP and C-suite leadership with consistent outstanding performance ratings. Sole point of contact for 60–70 cross-functional business stakeholders spanning Originations, Servicing, Recapture, and Compliance.
الخبرة
Senior Data Analyst — Data Science & Analytics
Designed and delivered the team's flagship Business Intelligence product — a real-time Power BI dashboard serving 250+ users, eliminating 15 daily manually produced reports and recovering the equivalent of approximately 40–50 FTEs of manual effort monthly across the sales organization. Implemented Dynamic Row-Level Security (Loan Officers through EVPs) using a Composite Model (DirectQuery for live operational data, Import Mode for reference tables); refactored the core data pipeline from 30+ minutes to under 2 minutes to enable near-real-time 15–20 minute dashboard refresh. Owned end-to-end development and daily production delivery of a multi-page SSRS PDF morning briefing distributed automatically to the CEO, EVPs, and SVPs — consolidating six to eight fragmented department reports into one authoritative executive scorecard covering pipeline, conversion rates, recapture metrics, headcount analytics, rolling 5-day trends, and six-month regression data. Led enterprise SQL Server performance optimization across a large portfolio of stored procedures and automated data pipelines, reducing overall SQL Server CPU utilization by approximately 40% through incremental loading architecture, data lake decoupling, and evidence-based job schedule re-design