Samandarov Javohir

Engineered the automation of key reporting processes, including an Early Warning System (EWS) that flags high-risk borrowers based on 'unlikely to pay' criteria, enabling proactive risk mitigation. Developed interactive Power BI dashboards with advanced DAX, transforming raw data into actionable insights for stakeholders. Utilized SQL, Python, and Power Automate for data extraction, transformation, and workflow automation to support advanced analytics initiatives. Produced in-depth analytical reports such as Portfolio Quality Analysis, NPL Inflow Projections, and Behavioral Analytics to help stakeholders assess portfolio health and manage financial risk.

• Working with business requirements and their clarification • DB modeling (database model for layer 3 Normal Form, "Star" and Data Marts) • Building hybrid DWH (by Inmon and Kimball) • SQL and PL/pgSQL query optimization • Dashboard and ETL Result testing and verification (Manual and automation testing using Apache JMeter, preparing checklists, bug reports, data mapping, data profiling, test strategy) • Developing Reports and Dashboards in Power BI Desktop

Implemented performance tuning on complex stored procedures, views, user defined functions and queries by creating proper indexes and optimizing the existing ones; Developed ETL solutions for integrating data from multiple sources like Flat Files (delimited, fixed width), Excel, SQL Server, Raw File, and DB2 into the central OLTP database; Experienced in AWS data architecture, including Amazon RDS, Amazon Redshift, and AWS Glue. Configured AWS platform for data pipelines, Glue, Amazon S3, and data lakes, and built workflows to automate data flow using AWS Glue. Built efficient ETL packages, using both SSIS and ADF2 pipelines for processing Fact and Dimension tables with complex transforms and SCD type 1/ type 2 changes; Build workflows to automate data flow using Python and ADF2.