Nihad Atakishiyev

Designed a content automation platform for mass-producing short-form videos across TikTok, Meta; architected an async EC2–GPU pipeline via Redis queues, dynamically scaling compute, and cutting costs by 60%+. • Engineered core systems with FastAPI, Next.js (TS), and Supabase, integrating Stripe for payments, AWS S3/EC2 for compute and storage, and FFmpeg for automated video generation. • Architected a SvelteKit–Supabase platform on Cloudflare Workers with Edge Function automation and RLS-secured Postgres.

• Developed core modules for Muvid, a creator-marketing platform connecting musicians with TikTok influencers, enabling campaign creation, performance tracking, and automated payouts through integrations with the TikTok API, Apify, and Tipalti. • Implemented scalable FastAPI backend services with Redis caching and MySQL (AWS RDS), handling high-volume data ingestion and asynchronous background processing using Celery with failover and retry mechanisms.

• Developed and customized Salesforce applications and integrations using Apex, Visualforce, and Lightning Web Components (LWC) to automate internal workflows and improve CRM usability. • Built interactive JavaScript-based components and optimized backend logic to enhance data handling and user experience across departments. • Achieved 90%+ unit test coverage with Jest for LWC, improving platform stability and deployment reliability within an Agile development cycle.

Developed core modules for Azerbaijan’s national COVID-19 mobility system serving 5M+ users with 99.9% uptime. Built data-driven apps and automated ETL pipelines using Python, Node.js, React, and MS SQL, integrating SSRS/SSIS for nationwide reporting. Implemented containerized CI/CD pipelines (Docker, Kubernetes) and a Laravel-based analytics platform embedding Tableau dashboards with centralized auth and multi-tenancy, cutting licensing costs by 75% (€15k/year).

Master’s Thesis – Automated Privacy Assessment for Android Applications: A DPV Visualization Approach Developed an automated framework that combines program slicing with interactive visualization to analyze user-data flows in Android apps and reveal GDPR compliance risks. The tool translates complex code-level behavior into intuitive visuals, bridging the gap between developers and legal experts. Co-authored the preprint Research Square, DOI: https://doi.org/10.21203/rs.3.rs-6323701/v1