An execution-first, impact-driven developer focused on building production-ready backend systems, optimizing high-performance relational schemas, and shipping end-to-end Machine Learning pipelines. I bridge the gap between complex data logic and scalable web architecture.

• The Core Architecture: Engineered an automated document-ingestion engine leveraging advanced Natural Language Processing (NLP) architectures via the spaCy framework to systematically structure random, unstructured text payloads.
• Linguistic Extraction: Built deep tokenization and custom classification pipelines to isolate, tag, and extract crucial entity matrices (contact details, specialized skills, professional timelines).
• Data Layer Optimization: Connected the extraction layer directly to a non-relational MongoDB database, mapping parsed resumes into dynamic JSON documents to minimize retrieval query latencies.

• Backend Pipeline: Deployed a lightweight, asynchronous text-processing engine powered by a modular Flask backend designed to receive low-latency API payloads.
• Algorithmic Mechanics: Coded high-efficiency algorithmic edit-distance constraints to compute dynamic text variations and serve context-aware, immediate corrections.
• Payload Cleansing: Layered complex Regular Expressions (Regex) at the entry point to sanitize data streams and eliminate syntax anomalies prior to interface rendering.

• ⚡ Version Control: Managed robust Git branching, remote migrations, and repository recovery architectures.
• 🗄️ Database Standard: Advanced schema manipulation, index implementation, and safe relationship constraints using MySQL.
• 🤝 Collaboration Model: Experienced leading cross-functional targets across corporate virtual settings, industrial labs, and national level bootcamps.

• 💼 LinkedIn: linkedin.com/in/aryan-sarkar
• 📧 Email: aryansarkar9400@gmail.com

"Moving local repositories into active development, one stable commit at a time."