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Mohammed Javed P

Data Analyst • Mumbai, Maharashtra, India • m****************@gmail.com • +91*******468 • linkedin.com/••••• • drivetube.ai/•••••

Professional Summary

Data Analyst with 2.2 years of experience specializing in SQL, Python (Pandas), and Power BI to deliver data validation, ETL pipelines, and stakeholder reporting for banking implementations. Experienced in validating core-banking extracts (TCS BaNCS), designing test datasets for functional and UAT cycles, and authoring repeatable data ingestion and reconciliation flows using Azure Data Factory and SQL. Skilled at instrumenting data quality checks with Python and SQL, provisioning analytics datasets in Azure Synapse Analytics, and building star-schema models and DAX measures in Power BI to surface KPIs. Proven collaborator with business analysts, QA and development teams to translate requirements into backend data setups and dashboards that improve data integrity and testing efficiency across core banking systems.

Technical Skills

Programming Language: Python,SQL
Databases: Azure Synapse Analytics
Cloud Platforms: Microsoft Azure,Azure Data Lake,Storage Gen2
Data Analysis & Visualization: Pandas,NumPy,Matplotlib,Power BI,DAX,Data Cleaning,Banking
Data Integration & ETL: Azure Data Factory
Compliance & Governance: Data Quality

Work Experience

Tata Consultancy Services
Mumbai, India
Data Analyst
Jun 2024 – Present
Worked on data validation, test-data provisioning and analytics for core banking implementations (TCS BaNCS) supporting SBI and related banking testing cycles.
Tech Stack: SQL, Python, Pandas, Azure Data Factory, Azure Data Lake Storage Gen2, Azure Synapse Analytics, Power BI, DAX
  • Analyzed and validated 100+ banking datasets daily using advanced SQL (joins, subqueries, CASE) to detect data discrepancies and support root-cause analysis for BANCS extracts.
  • Designed and structured test datasets for SBI core-banking implementations to support functional and integration testing and multiple UAT cycles, ensuring realistic data coverage for BANCS scenarios.
  • Authored Azure Data Factory pipelines to ingest BANCS extracts into Azure Data Lake Storage Gen2, establishing repeatable raw-data landing patterns for downstream processing.
  • Developed SQL reconciliation scripts and Python (Pandas) utilities to reconcile transaction records and implement repeatable data quality checks across environments.
  • Implemented reporting-ready tables in Azure Synapse Analytics to provision analytics datasets consumed by stakeholders and testing dashboards.
  • Built Power BI reports with star-schema models and DAX measures to surface KPIs, enable defect-tracking dashboards, and support stakeholder decision-making during testing.

Projects

Business 360 Dashboard – AtliQ Hardware Link | Oct 2025 – Dec 2025
Tools Used: Power BI, SQL, Excel, DAX
  • Developed a multi-functional Power BI dashboard analyzing global sales trends for brick-and-mortar and e-commerce channels, integrating data from Excel/CSV files and SQL databases.
  • Built comprehensive star-schema data models and interactive visualizations to enable cross-filtering and drill-down analysis across product, region, and channel dimensions.
  • Optimized report performance using DAX Studio to improve query responsiveness and reduce refresh times.
  • Enabled data-driven decision-making through dynamic filtering, drill-throughs, and KPI cards surfaced to sales and operations stakeholders.
Hotel Booking Revenue Analysis – Python Data Analytics Link | Dec 2025 – Jan 2026
Tools Used: Python, Pandas, NumPy, Matplotlib
  • Analyzed 100K+ hotel booking records across five relational datasets using Python (Pandas) to perform data cleaning, validation, and exploratory data analysis.
  • Built a star-schema data model joining fact and dimension tables using optimized merge and groupby operations to enable KPI analysis for revenue and occupancy.
  • Computed key business metrics including total revenue and average revenue per booking and detected outliers using statistical methods.
  • Conducted time-series and segmentation analysis across city, hotel category, and room class to uncover seasonal demand patterns and actionable insights.

Education

Srinivasa Ramanujan Institute of Technology
Bachelor of Technology in Computer Science and Engineering • Anantapur, Andhra Pradesh, India • Aug 2019 – Jun 2023

Certifications

Diploma in Data Science & Applications — IIT Madras • Sep 2023
SQL: Beginner to Advanced for Data Professionals — Codebasics • Jan 2024

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