I'm a Cloud Data Engineer with 3 years of experience across data engineering, analytics, and software development. M.Tech from IIT Kanpur. My work spans building ELT pipelines, real-time ingestion platforms, and analytical data models on AWS, Azure, and Snowflake. I design Medallion Architecture data layers, build dbt transformation pipelines, and work across the full modern data stack — from ingestion to reporting. Before working in data engineering, I worked as a Data Scientist at Agatsa Software, developing deep learning models (CNN-LSTM) for ECG classification and leading a team of 5 engineers. That experience gave me a strong foundation in data quality, structured experimentation, and cross-functional collaboration. What I work with: → Languages: Python, SQL → Big Data: PySpark, Apache Spark, Kafka, Batch & Near-Real-Time Processing → Cloud: AWS (S3, IAM), Microsoft Azure (ADF, ADLS Gen2, Event Hubs) → Warehousing: Snowflake, dbt Core, Medallion Architecture, Star Schema, SCD Type 2 → DevOps: Git, REST APIs, FastAPI → AI/ML: Generative AI, LLM Applications, Deep Learning While building my own portfolio, I noticed most resources teach you how to use tools — but not which projects to build to get hired. So I wrote Data Engineering Project Ideas for Career Growth — 50+ real-world projects across 5 experience levels, with built-in architecture blueprints, tech stacks, and interview scripts. I can help you with: → Choosing the right projects for your target role → Portfolio and GitHub reviews → Data engineering interview preparation → Tech stack and career direction guidance