abhinav = {
"role" : "Data Engineer @ BlackRock",
"location" : "India 🇮🇳 · Open to Global / Remote Opportunities 🌍",
"experience" : "5+ years — Finance, Retail/CPG, Aviation, Cybersecurity",
"i_build" : ["Medallion lakehouses", "streaming pipelines", "batch ELT"],
"learning" : ["GenAI", "Agentic AI", "LangChain", "RAG", "MCP"],
"ask_me_about": ["Azure", "Databricks", "PySpark", "Airflow", "Snowflake"],
}- 🔭 Building production data pipelines on an Azure-first stack.
- 🌱 Currently going deep on GenAI / Agentic AI systems.
- 🎯 Open to Senior Data Engineer, GenAI Data Engineer & GenAI Developer roles.
- 📫 Reach me: abhinavsuman0204@gmail.com
5+ years delivering data engineering across Financial Services, Retail/CPG, Aviation, and Cybersecurity — building batch & streaming pipelines, lakehouses, and dimensional models for global enterprises (clients include Loblaw, PepsiCo).
Databricks Data Engineer Professional · Azure DP-203 · SnowPro Core · MS Fabric Analytics Engineer Associate · Astronomer Airflow (x2)
🟢 Live · 🟡 In progress · 🔵 Planned
| Project | Stack | What it does | Status |
|---|---|---|---|
| Databricks Medallion Architecture | Databricks · Delta · PySpark | Bronze→Silver→Gold lakehouse with incremental loads | 🟢 Live |
| Tokyo Olympic Azure DE Project | ADF · Databricks · Synapse · ADLS | End-to-end Azure pipeline: ingest → transform → analyze | 🟢 Live |
| Generative AI Masters | LangChain · RAG · Vector DBs · Agents | Hands-on GenAI systems bootcamp — prompting → agents | 🟡 In progress |
| Python — Back to Basics | Python | Core Python, data science, visualization, web | 🟢 Live |
| DSA in Python | Python | Curated DSA problems with clean solutions & tests | 🟡 Ongoing |
| Git Concepts Revision | Git | Quick-reference notes on Git workflows | 🟢 Live |
Now: Generative AI Masters — building RAG & agentic workflows 🤖
🔄 Latest activity (auto-updates every 12 hours):


