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Data Analyst with less than a year in SQL, Python, and Power BI
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Detail-oriented Data Analyst with hands-on experience in SQL, Python, and Power BI, specializing in data wrangling, data cleaning, data transformation, and end-to-end ETL pipeline development. Proficient in writing complex SQL queries (CTES, Window Functions, Stored Procedures), building DAX-driven Power BI dashboards, and performing exploratory data analysis (EDA) to surface actionable business insights. Experienced in star-schema data modelling, KPI design, and statistical analysis. Actively leverages AI productivity tools (ChatGPT, Claude) to accelerate research and query writing.
Raghu Engineering College
Bachelor of Technology · Electronics & Communication Engineering
December 1, 2021 – April 1, 2025
Pandit Junior College
M.P.C · Mathematics, Physics, Chemistry
June 1, 2019 – March 1, 2021
Sales Performance Analysis Dashboard
June 1, 2026 – Present
• Designed and developed a multi-page interactive Power BI dashboard tracking sales trends, product performance, and customer-level metrics using drill-through pages and cross-filter visuals. • Built advanced DAX measures for time-intelligence KPIs (YoY growth, MoM comparisons), enabling period-based performance benchmarking across product lines and customer segments. • Implemented star-schema data modelling with defined relationships and configured Row-Level Security (RLS) roles to enforce data governance and restrict visibility per user group.
Multi-Brand Marketplace SQL Project
June 1, 2026 – Present
• Architected a normalized 10-table relational database schema (Sellers, Products, Orders, Customers, Payments, Inventory, Shipments) modelled on real-world e-commerce platforms. • Wrote complex multi-table JOIN queries and CTEs to generate seller performance reports, customer order histories, and category-level revenue summaries. • Reduced query execution time by ~50% by applying covering and composite indexes, validated through SSMS execution plan analysis.
E-Commerce Sales Analysis - Python ETL & EDA
June 1, 2026 – Present
• Built an end-to-end ETL pipeline to ingest, clean, and transform 1,000+ transaction records, reducing data inconsistencies by 30% through systematic data wrangling and validation. • Performed EDA to surface revenue trends, profit margins, and regional performance patterns; automated KPI report generation using Matplotlib and Seaborn, enabling 100% repeatable output.
Insurance Claims & Policy Analysis Dashboard
June 1, 2026 – Present
• Analyzed claim frequency trends, active vs. inactive policy ratios, and customer age segmentation using DAX-calculated columns and synchronized slicers with bookmarks. • Standardized inconsistent date formats and normalized policy data across multiple source tables via Power Query transformations, cutting manual report preparation time by ~40%.
SQL Certification
SkillUp by GeeksforGeeks
June 1, 2026 – Present
Data Analytics Essentials
Cisco
June 1, 2026 – Present
Microsoft Power BI Data Analyst (PL-300)
Unknown
June 1, 2026 – Present
SQL and Relational Databases 101 (DB0101EN)
IBM Skills Network
February 1, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong alignment with the Data Analyst role, covering key areas like e-commerce sales analysis, marketplace data, and insurance claims. The diversity of projects (SQL, Python ETL, Power BI dashboards) indicates a broad skill set and adaptability. The pursuit of multiple certifications (SQL, Data Analytics Essentials, Power BI Data Analyst) shows a commitment to continuous learning and professional development, which is a positive cultural indicator. However, the lack of professional experience means cultural fit is primarily inferred from project work and self-driven learning.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a detail-oriented approach to data analysis, focusing on data quality, efficiency improvements (e.g., reducing query execution time, cutting manual report preparation time), and delivering actionable insights. The use of AI tools suggests an adaptive and efficient work attitude. However, without completed psychometric or English tests, a comprehensive assessment of soft skills, logical reasoning, stress handling, and team collaboration is not possible.