May 2023 – Present · 2 yrs 10 mos · Delhi, India · On-site

• Tech Stack: Python, Flask, Django, Neo4j, Elasticsearch, SQL Server, MySQL, Pandas, NumPy, Dask, Airflow, PySpark, Databricks, Power BI, Kibana, AWS S3, LLM (Llama), NLP, Jupyter, Git, Linux, ExcelKey Responsibilities & Achievements:
• 🔹 Developed scalable data ingestion pipelines to process structured and unstructured data (CSV, Excel, DOC, DOCX, PDF, XML, JSON, image-based text extraction) into Neo4j and Elasticsearch databases.
• 🔹 Designed and deployed RESTful APIs using Flask, FastAPI, and Django, powering backend modules for real-time data access and dashboards.
• 🔹 Built custom ETL frameworks and scheduled pipelines using Apache Airflow, handling large-scale data movement across internal systems and client servers.
• 🔹 Worked on PySpark and Databricks for distributed data processing and performance optimization.
• 🔹 Created automated reports, analytics dashboards, and widgets using Power BI, Kibana, and Python visualization libraries (Matplotlib, Seaborn).
• 🔹 Integrated NLP and LLM (LLaMA) modules to extract intelligence from text data, contributing to smart decision-making layers in software.
• 🔹 Implemented cron jobs, automation scripts, and data validation modules for production pipelines on Linux (Ubuntu, CentOS) systems using Putty, Jupyter, and WinSCP.
• 🔹 Contributed to prediction modules and ML model pipelines using scikit-learn, improving decision accuracy.
• 🔹 Worked on GIS-based mapping modules, plotting pushpins on maps using latitude/longitude for location intelligence.
• 🔹 Improved code performance, reduced ingestion time, and ensured end-to-end pipeline monitoring and debugging.