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Sonawane250398/README.md

Yash Sonawane

Business Analyst | Financial Data Integrity | SQL Reconciliation | Source-to-Report Validation

Fullerton, CA · Available for immediate hire

LinkedIn Portfolio Email

What I do

I find the reconciliation breaks that don't surface until month-end, then build the controls that catch them at the source.

4+ years validating financial data across source, ETL, and reporting layers. The work that matters is upstream: catching mismatches, missing records, and balance variances before they reach anyone who asked for the numbers.

  • Built SQL reconciliation frameworks validating 5,000+ records monthly across 3 reporting layers — discrepancies down 20%, investigation time down 30%
  • Caught 80 exceptions across 1,000 transactions using a Python severity engine — zero manual steps, audit-ready output
  • Delivered 6 consecutive zero-defect releases across 3 business units — UAT to deployment with no rollbacks
  • Eliminated 6–8 hours of weekly manual reporting through automated Tableau and Python pipelines

Core skills

Financial Systems SQL reconciliation · Source-to-report validation · ETL validation · Exception classification · Variance analysis · Data lineage · Financial reporting · Reporting controls

Business Analysis BRD · User stories · Traceability matrices · UAT design · Defect tracking · Release readiness · SDLC · Cross-functional requirements alignment

Quality Assurance UAT test scenario design · Defect documentation · Cross-system validation · Release readiness checks

Tools SQL · Python · Pandas · Tableau · Power BI · Advanced Excel · Dash · Plotly · Jira · Confluence · Git · Agile/Scrum

Tech stack

Python SQL Pandas Tableau Power BI Dash Plotly Advanced Excel Jira Confluence Git

Featured projects

Project What it does Links
Financial Reporting Failure Detection System 80 exceptions caught across 1,000 transactions · 5 failure types · zero manual steps · audit-ready output before any data reaches reporting GitHub
Financial Analytics Dashboard $174M analyzed · 8 interactive charts · profit margins tracked 39% to 47% across 5 segments · live deployed on Render Live · GitHub
SQL Reconciliation Platform 3-layer source-to-report validation · missing records, duplicates, GL mapping errors, balance variances detected before final reporting GitHub
UAT Release Framework Full BA release pack · traceability matrix · defect tracking · zero open defects at UAT sign-off GitHub
Reporting Controls Model 5 financial domains monitored · variance thresholds standardized · every exception flagged with control checkpoint reference before management review GitHub
Requirements Traceability Matrix 13 functional requirements mapped to user stories, test cases, sprint delivery · 100% coverage across 4 sprints · zero open defects at UAT sign-off GitHub

Certifications

  • Google Advanced Data Analytics Capstone — Google | Coursera (Apr 2026)
  • SQL Advanced — HackerRank (Apr 2026)
  • SQL for Data Analysis — Kaggle: window functions, CTEs, query optimization, BigQuery (Mar 2026)
  • Pandas — Kaggle: data cleaning, transformation, aggregation (Mar 2026)
  • Microsoft Data Analytics — Microsoft (Mar 2026)

GitHub Stats

GitHub Streak

Open to BSA · Financial Systems Analyst · Data Analyst roles in fintech, banking & enterprise SaaS

Portfolio · LinkedIn · Email

Pinned Loading

  1. financial-failure-detection-system financial-failure-detection-system Public

    End-to-end automated system that detects financial reporting failures across a 3-layer data pipeline (Source → ETL → Reporting). Runs 5 SQL reconciliation checks, classifies 80 exceptions by severi…

    Python

  2. financial-dashboard financial-dashboard Public

    Interactive financial analytics dashboard built with Python, Dash & Plotly — analyzing $174M in sales across segments, countries & years with 8 dynamic charts

    Python

  3. source-to-report-financial-reconciliation-platform source-to-report-financial-reconciliation-platform Public

    SQL-based reconciliation workflow comparing source, transformed, and reporting-layer finance data to detect missing records, duplicates, mapping errors, and balance variances.

  4. financial-reporting-uat-release-readiness-framework financial-reporting-uat-release-readiness-framework Public

    Structured UAT framework for a financial reporting enhancement — including user stories, acceptance criteria, test cases, defect tracking, and release-readiness checkpoints.

  5. financial-reporting-controls-monitoring-model financial-reporting-controls-monitoring-model Public

    Standardized SQL validation layer running automated control checkpoints across 5 financial reporting domains — Revenue, P&L, Inventory, Expenses, and Payroll.

  6. requirements-traceability-matrix requirements-traceability-matrix Public

    Requirements Traceability Matrix mapping 13 functional requirements to user stories, test cases, and sprint delivery — covering a SQL-based financial reconciliation system end-to-end.