class DataEngineer:
    def __init__(self):
        self.name        = "Mohammad Asad Rahmani"
        self.role        = "Fresher | Data Engineer & Cloud Engineer"
        self.education   = "B.Tech CSE (AI/ML) — Techno India University, Kolkata"
        self.cgpa        = 7.96
        self.graduating  = "May 2026"
        self.location    = "Kolkata, India"
        self.open_to     = ["Data Engineering", "Cloud Engineering", "ETL Development"]
        self.cities      = ["Kolkata", "Hyderabad", "Mumbai"]

    def current_focus(self):
        return [
            "Building production-grade ETL pipelines on GCP & AWS",
            "Designing serverless architectures with Lambda & BigQuery",
            "Mentoring 750+ students as Google Cloud Arcade Facilitator",
            "Exploring Apache Spark for large-scale data processing"
        ]

me = DataEngineer()

GCP · BigQuery · Apache Spark · Airflow · Docker

Engineered a distributed data processing platform capable of handling millions of records. Designed multi-stage ETL pipelines with Airflow orchestration, Spark transformation layers, and BigQuery as the analytical warehouse. Achieved significant query performance improvements through partitioning and clustering strategies.

AWS Lambda · S3 · SNS · Terraform · Python

Built a fully serverless event-driven data pipeline on AWS, provisioned entirely via Terraform IaC. Implemented S3-triggered Lambda functions with SNS alerting for real-time processing and fault notification. Zero-downtime deployments with automated rollback strategies.

Python · Mage.ai · PostgreSQL · Docker

Developed an intelligent financial transaction processing system using Mage.ai for pipeline orchestration. Implemented ML-based categorisation logic with a fully Dockerised deployment. Designed for scalability with modular pipeline architecture.

Python · XGBoost · Random Forest · Flask · Docker · GCP

Built end-to-end ML pipeline for healthcare outcome prediction achieving 94% accuracy using ensemble methods (XGBoost + Random Forest). Deployed as a containerised Flask REST API on GCP with automated retraining workflows.

I'm actively seeking fresher roles in Data Engineering and Cloud Engineering based in Kolkata, Hyderabad, or Mumbai.

I bring hands-on project experience with production-grade cloud tooling — GCP, BigQuery, AWS, Spark, Airflow, Docker, and Terraform — paired with strong Python fundamentals and a genuine passion for building reliable data infrastructure.

📩 Let's talk: asadrahmani3101@gmail.com | LinkedIn

Foundations        →  ETL / ELT          →  Cloud Native       →  Advanced
─────────────────     ─────────────────     ─────────────────     ─────────────────
✅ Python           ✅ Apache Airflow      ✅ GCP + BigQuery     🔄 Apache Kafka
✅ SQL / NoSQL      ✅ Mage.ai Pipelines   ✅ AWS (Lambda/S3)    🔄 dbt (Data Build)
✅ PostgreSQL       ✅ Apache Spark        ✅ Terraform IaC      📌 Databricks
✅ Docker           ✅ ETL Best Practices  ✅ Cloud Storage      📌 Snowflake

✅ Completed · 🔄 In Progress · 📌 Planned

"Data is the new oil — I'm here to refine it."

⭐ If you find my work interesting, consider giving a star!