Digital Operations Engineer · Python Automation Architect · Audio Engineer
I build Python tools that automate music distribution pipelines — turning 45-minute manual workflows into 2-minute automated runs, increasing team throughput by 300%.
A fully autonomous distribution pipeline — from a single CSV of track metadata to packaged DDEX ERN 3.8.2 deliveries across TikTok, YouTube Content ID, and Facebook. Includes genre-aware routing, Playwright-based Octolivery automation, and multi-format audio conversion.
Upload any CSV/Excel and transform data using natural language. Two-stage prompt refinement with Google Gemini, preview before commit, dual export. Deployed on Streamlit Community Cloud.
Production-grade parallel batch downloader for YouTube, Udio, Facebook & Instagram Reels. Retry logic with exponential backoff, multi-format audio conversion (MP3/FLAC/WAV), thumbnail processing, and manifest tracking.
Subtitle editor with English→Arabic AI translation using Google Gemini. Multi-key rotation, model fallback chain (3 models), batch processing of 12 blocks per API call, inline editing, and rate limit handling.
Six battle-tested Python utilities for music catalog operations: DSP data transformer, UPC/ISRC file organizer, DDEX packager, Anghami ID scraper, YouTube metadata enricher, and FLAC duration extractor.
Resolve YouTube Content ID asset IDs to video URLs using the YouTube Data API v3. Two-pass verification (Search API → Snippet confirmation), batch CSV processing, and quota-aware rate limiting.
Flask web application for uploading two CSV files and finding correlations, matches, and discrepancies between datasets. Built for cross-referencing music catalog data across different DSP platforms.