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Data Analyst with 4+ years in SQL, Python, Tableau & Data-driven Problem Solving
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Aspiring Data Analyst with 4.6 years of professional experience working with large-scale transactional data and data-driven problem solving. Skilled in SQL, MySQL, Excel, Python, Tableau, and Exploratory Data Analysis (EDA) for data validation, workflow analysis, and insight generation. Experienced in analyzing production data, identifying inconsistencies, and supporting business operations. Previously worked as a Software Engineer in enterprise application environments.
SDM College of Engineering and Technology
Electrical and Electronics Engineering · Electrical and Electronics Engineering
August 1, 2016 – June 30, 2020
Manhattan Associates
Software Engineer
January 1, 2023 – December 31, 2025
India
Wipro Technologies
Project Engineer
January 1, 2021 – December 31, 2023
India
Retail Consumer Behavior & Marketing Optimization
January 1, 2025 – December 31, 2025
Leveraged Python (Pandas) to perform Exploratory Data Analysis (EDA) and data profiling; handled missing values in the Review Rating column and standardized categorical features across 3,900+ records to ensure analytical accuracy. Migrated cleaned datasets into an SQL database, designing a structured schema to simulate real-world business transactions and enable complex relational querying. Developed advanced SQL queries to categorize customers into segments (e.g., "Loyal," "At-Risk") and analyzed the correlation between promo code usage, shipping types, and purchase frequency. Engineered an interactive Power BI dashboard featuring dynamic filters for demographics (Age, Gender, Location) and sales channels, transforming raw metrics into visual stories for stakeholders. Identified high-revenue opportunities among express-shipping users and recommended a shift toward subscription-based loyalty models to maximize long-term Customer Lifetime Value (CLV).
Apparel Store Annual Sales Performance Analysis
January 1, 2025 – December 31, 2025
Processed a dataset of 31,000+ rows, utilizing Excel functions to scrub null values and standardize inconsistent entries (e.g., mapping 'M/W' to 'Men/Women') for 100% data consistency. Engineered new data columns, including Age Bucketing and Date-to-Month extraction, to facilitate deeper trend analysis and time-series forecasting. Performed extensive Exploratory Data Analysis (EDA) using Pivot Tables to pinpoint the highest-revenue states, peak sales months, and dominant customer segments. Developed a comprehensive Sales Performance Report featuring dynamic Pivot Charts and Slicers, allowing users to filter performance by Sales Channel (Amazon, Flipkart, etc.), Category, and Month. Identified Adult Women as the primary demographic and Amazon as the top sales channel, providing a data-backed foundation for targeted marketing and inventory planning for 2023.
Cultural Fit Analysis
The candidate's background as a Software Engineer transitioning into a Data Analyst role shows adaptability and a drive for continuous learning. Their personal projects demonstrate initiative and a strong interest in data analysis, aligning well with a data-driven culture. The diversity of tools used (Excel, Python, SQL, Power BI) and the application of data analysis to different business scenarios (apparel sales, retail consumer behavior) suggest a broad skill set and a willingness to tackle varied challenges. The experience in enterprise environments (Manhattan Associates, Wipro Technologies) indicates familiarity with structured work processes and collaboration.
Soft Skills & Operational Fit
The candidate's experience in collaborating with cross-functional teams and business stakeholders in previous software engineering roles indicates good communication and teamwork skills. Their involvement in Go-Live support and troubleshooting production issues suggests problem-solving abilities and a proactive attitude towards operational stability. The project descriptions highlight an ability to translate technical analysis into strategic business recommendations, indicating a business-oriented mindset.