Niraj Kadam

C-DAC PG-DBDA & CS Graduate | Data Engineer & AI/ML Specialist | PySpark, Spark, FastAPI, Docker, SQL, Ollama AI, LangChain | Building Scalable Data Lakehouses & ML Pipelines

Hyderabad, Telangana, India

@niraj_kadam

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About

Results-driven Computer Engineering graduate and PG-DBDA (Post Graduate Diploma in Big Data Analytics) candidate at C-DAC specializing in Data Engineering, Machine Learning, and Big Data Technologies. Experienced in developing automated data pipelines, multi-agent AI lakehouse platforms, and security assessment tools. CORE TECHNICAL SKILLS: • Big Data & Cloud: Apache Spark, PySpark, Hadoop, HDFS, Hive, Kafka, GCP Cloud Fundamentals • Data Engineering: ETL Pipelines, Data Warehousing, Parquet, MinIO Object Storage, Schema Normalization • AI & Machine Learning: Generative AI, LLMs, LangChain, Multi-Agent Systems, Ollama AI, RAG, Scikit-Learn, Pandas, NumPy • Databases & APIs: PostgreSQL, MySQL, MongoDB, FastAPI, Flask, REST APIs • Tools & Security: Docker, Git, Linux, Nmap, Gobuster, ADB, VirusTotal API, OWASP Standards KEY PROJECTS: 1. Multi-Agent AI Data Lakehouse Platform: Built a multi-agent ETL pipeline using PySpark, FastAPI, MinIO, Parquet, and LangChain/Ollama AI to automate structured payment extraction and transaction classification. 2. CyberSquad Security Auditing Tool: Engineered a Python-backed security auditing tool integrating Nmap, Gobuster, ADB, VirusTotal APIs, and Ollama AI for automated CVE analysis and PDF report generation. EDUCATION & CERTIFICATIONS: • C-DAC ACTS: Post Graduate Diploma in Big Data Analytics (PG-DBDA) [2026] • Mumbai University: B.E. in Computer Engineering [2025] • Google Cloud Computing Fundamentals & Google Cybersecurity Professional Certificates

Education

Post Graduate Diploma (or PG Diploma)

Centre for Development of Advanced Computing

Big Data Analytics (PG-DBDA) · Feb 2026 – Aug 2026
Bachelor of Engineering (B.E.) (or B.Tech)

Smt. Indira Gandhi College of Engineering · University of Mumbai

Computer Engineering · 2021 – 2025

Skills

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