𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗔𝘁𝘁𝗲𝗻𝗱𝗮𝗻𝗰𝗲 𝗔𝘂𝗱𝗶𝘁 𝗦𝘆𝘀𝘁𝗲𝗺 (𝗣𝘆𝘁𝗵𝗼𝗻 𝗘𝗧𝗟)

𝗗𝗲𝘀𝗰𝗿𝗶𝗽𝘁𝗶𝗼𝗻: To enforce strict shift policies without increasing administrative workload, I engineered a specialized Python ETL pipeline that autonomously audits employee attendance. Management previously wasted hours cross-referencing raw door access logs with shift schedules. I automated this entirely: the system ingests raw data streams, detects anomalies (late arrivals, early departures, missing check-ins) using Pandas, and delivers detailed compliance reports to management—eliminating manual oversight entirely.

𝗞𝗲𝘆 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝗮𝗯𝗹𝗲𝘀:
•𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗗𝗮𝘁𝗮 𝗜𝗻𝗴𝗲𝘀𝘁𝗶𝗼𝗻: Built a robust listener using imap-tools that intercepts raw email logs from access control hardware, extracting attachments and parsing unstructured data automatically.
• 𝗣𝗮𝗻𝗱𝗮𝘀 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗘𝗻𝗴𝗶𝗻𝗲: Developed complex data transformation logic with Python Pandas to merge door logs with employee rosters, calculating precise work hours and flagging violations based on custom business rules.
• 𝗥𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: Integrated Jinja2 templating and PDFKit to generate professional, branded PDF reports from analyzed data, which are then securely dispatched to HR via SMTP.
• 𝗭𝗲𝗿𝗼-𝗧𝗼𝘂𝗰𝗵 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻: Designed the system to run as a “set-and-forget” background service, handling errors gracefully and ensuring 100% daily reporting uptime.

• Skills: Python 3 • Pandas (Data Analysis) • IMAP Protocol • Jinja2 • PDFKit • Automated Reporting