Muhammad Noor e Alam
Database Developer @United Wholesale Mortgage
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WORK HISTORY
Database Developer @United Wholesale Mortgage
MI, US
Designed, developed, and optimized SQL queries, stored procedures, and functions to ensure efficient data processing and reporting.• Developed and maintained ETL pipelines using SSIS, Talend, and DBT, supporting data integration from multiple sources into SQL Server and Big Query.• Performed database performance tuning, query optimization, and indexing strategies to improve system efficiency.• Created and managed reports and dashboards using Power BI and SSRS, enabling stakeholders to make data-driven decisions.• Ensured data integrity, consistency, and accuracy through rigorous validation, back-end testing, and cross-team collaboration.• Worked with cloud platforms (GCP & Azure) to design scalable database solutions and manage data workflows.• Contributed to CI/CD processes and version control using GitHub, Bitbucket, and JIRA, ensuring smooth database development, deployment, and collaboration.• Collaborated with business analysts, developers, and QA teams to translate business requirements into technical solutions.• Leveraged prior QA experience to enhance data validation, testing strategies, and quality assurance for database systems.• Maintained Requirement Traceability Matrix (RTM) and project documentation using JIRA for efficient project tracking and collaboration.
EDUCATION
Government Titumir College
Bachelor of Arts - BA, English Literature
Government Titumir College
Master of Arts - MA, English Literature
Government Titumir College
Diploma , Information Technology
ABOUT MUHAMMAD NOOR E ALAM
I\'m a data professional with 3 years of Analytics Engineering and 1.5 years of QA experience, specializing in GCP and dbt — designing and building cloud-based data pipelines, Medallion architectures, and compliance reporting systems at United Wholesale Mortgage — the #1 mortgage lender in the U.S. My day-to-day work sits at the intersection of data engineering and analytics engineering. I independently designed and built a full Medallion data lake on GCP for HMDA compliance data — 50+ dbt models from scratch, covering Landing through Serve layers — with BigQuery partitioning and clustering applied to every incremental model for cost efficiency and performance. I also reduced a critical Internal Audit stored procedure runtime by over 80% through SQL performance tuning and query optimization. Before moving into data engineering, I spent 3 years as a Data QA Analyst at UWM, where I built automated test frameworks using Selenium and C#, performed functional and UI system testing for mortgage fee workflows, validated Talend ETL pipelines and Power BI dashboards, and ensured data accuracy across HMDA and compliance datasets using SQL. That QA foundation gave me a deep appreciation for data quality and testing rigor that I carry into every pipeline I build today. Beyond building, I focus on quality and governance: embedded dbt testing, data lineage, referential integrity checks, and thorough documentation are part of every pipeline I own. I maintain 25+ SSRS reports, 2 Power BI dashboards (including an Appraisal Bias detection tool built for fair lending compliance), and 5 Talend ETL jobs — all serving Legal, Compliance, and Internal Audit stakeholders. I\'m also genuinely curious about AI. I\'ve built agents with n8n, explored LangChain and LangGraph, and have working knowledge of RAG, vector databases, and MCP — understanding how structured data pipelines connect to AI-powered applications. I actively use GitHub Copilot and Claude Code in my workflow. Currently exploring new opportunities in Data Engineering, Analytics Engineering, and Database Development. Core stack: dbt · GCP · BigQuery · SQL Server · Talend · SSIS · Power BI · SSRS · Terraform · Selenium · C# · GitHub
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