Key Responsibilities  Extract, clean, transform, and analyze large datasets using Python and SQL to generate business-ready insights  Build and maintain automated analytical workflows, reports, and scheduled emailers for business stakeholders  Develop reusable data processing scripts and frameworks to support recurring analyses  Perform retail-focused analyses including: o Best deal / promotion effectiveness o Size & assortment mix analysis o Sales, inventory, and demand trend analysis  Convert analytical outputs into clear narratives, summaries, and visualizations for senior stakeholders  Partner with business teams to understand requirements and translate them into analytical solutions  Ensure data quality, validation checks, and performance optimization across pipelines and reports Required Skills & Experience  3–5 years of experience in Data Analysis / Analytics Engineering  Strong proficiency in Python, with advanced usage of Pandas  Strong SQL skills for complex querying and data analysis  Excellent logic building and problem-solving abilities  Proven experience working in or supporting the retail / consumer business domain  Ability to convert data into insightful, decision-oriented outputs Technical Stack Programming & Data Processing  Python  Pandas  SQL Data Analysis & Visualization  Exploratory Data Analysis (EDA)  Matplotlib  Data validation and insight reporting Automation & Tools  Outlook automation using win32com  Scheduled reporting and automated emailers  Libraries: tqdm, datetime, os, PIL Version Control  Git / GitHub / GitLab