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.
<p>Acted as the primary analytics lead for a 250+ user stakeholder group, designing and delivering the team’s flagship Power BI dashboard that replaced 15 manually produced reports, recovering the equivalent of approximately 40–50 FTEs of manual analytical effort monthly through a 5-tier Dynamic Row-Level Security model.<br>
Owned end-to-end development of a multi-page executive analytical brief, automatically distributed daily to C-suite and senior leadership — consolidating six to eight fragmented data sources into one authoritative, decision-ready evidence summary with trend, performance, and regression-based forecasting.<br>
Led an enterprise-wide analytics performance program, reducing analytical processing overhead by approximately 40% and cutting a core data ingestion workflow runtime by approximately 83% (40–45 minutes to 7–8 minutes) through incremental-loading architecture and evidence-based workflow redesign.<br>
Reduced enterprise analytics model refresh time from 1.5 hours to approximately 20 minutes through data-layer pre-aggregation and incremental refresh configuration; managed full platform lifecycle (development, UAT, production) including access governance and asset endorsement.<br>
Designed a data quality and validation safeguard embedded across all core analytical pipelines, preventing reporting failures during upstream data issues and ensuring uninterrupted delivery of decision-support outputs.<br>
Integrated third-party external datasets with internal portfolio data to segment opportunities using structured variables and behavioral signals; diagnosed root causes through evidence-based analysis and presented data-backed recommendations directly to senior and executive leadership.<br>
Modernized a legacy analytical reporting system into a maintainable architecture through structured business logic analysis, parallel validation, and stakeholder sign-off — strengthening governance and reducing long-term technical risk.<br>
Owned recurring regulatory reporting submissions; built standardized scorecards for cross-functional review; mentored junior analysts and conducted peer reviews to maintain analytical quality before every release.</p>
<p>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.</p><p> 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.</p><p> 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.</p><p> 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</p>
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