name: Rishabh Kumar Singh
role: Data Engineer (student) — pipelines, warehousing, AI-augmented analytics
education: B.Tech CSE (AI), KIET Group of Institutions · 2024 → 2028
location: Delhi, India
certified: AWS Certified Data Engineer – Associate (DEA-C01)
open_source: Apache Airflow contributor — see live merged-PR count below
stack: [Snowflake, dbt, Airflow, AWS, Python, SQL, Docker]
learning: [Apache Spark, System Design, Advanced dbt + CI/CD]
status: Open to Data Engineering / Analytics / Cloud internshipsI build batch data platforms the way production teams do: layered models, tested transformations, orchestrated and containerised, with an AI layer on top for people who don't write SQL.
🌐 Open-source contributor to Apache Airflow — pull requests merged into the orchestrator behind my own pipelines.
| 🌐 Open Source |  in Apache Airflow |
| ☁️ Certified | AWS Certified Data Engineer – Associate (DEA-C01) and Cloud Practitioner (CLF-C02) |
| 📦 Scale | Pipeline handling 10M+ orders · 23M+ order items · 300K+ reviews |
| 🤖 AI on the warehouse | LLM review enrichment, RAG review chat, and NL→SQL with a SELECT-only guard |
| 🥇 Leadership | 1st Prize, InnoTech Tech Fest — led the ZeroMile logistics concept |
| 🧪 Industry exposure | Software QA Engineering intern at FabHotels |
Python AWS S3 Snowflake dbt Apache Airflow Docker OpenAI Streamlit
A production-style batch platform that takes raw CSVs to AI-powered analytics.
flowchart LR
A[Raw CSVs] --> B[(AWS S3)]
B --> C[Snowflake<br/>Bronze]
C --> D[dbt<br/>Silver]
D --> E[dbt<br/>Gold]
E --> F[OpenAI<br/>Enrichment · RAG · NL→SQL]
F --> G[Streamlit App]
H{{Airflow DAG<br/>daily · 4 tasks}} -.orchestrates.-> C
H -.-> D
H -.-> E
H -.-> F
| Area | What it does |
|---|---|
| Architecture | Medallion (Bronze → Silver → Gold), 15+ dbt models |
| Loading | Incremental MERGE, SCD Type 2 snapshot |
| Quality | Automated dbt tests across every layer |
| Orchestration | Daily 4-task Airflow DAG, fully Dockerized |
| AI layer | LLM review enrichment · RAG review chat · NL→SQL with SELECT-only safety guard |
I contribute to Apache Airflow, the workflow orchestrator I use daily in my own data pipelines. My pull requests are reviewed by maintainers and merged upstream; the badge above counts them live.
| Project | Stack | Summary |
|---|---|---|
| 📊 Sales Data Analysis Dashboard | Python SQL Pandas Power BI |
ETL workflow for raw sales data, with Power BI dashboards for KPIs, revenue trends and regional performance. |
| 👨🏫 Teacher Data Management System | Java Spring Boot MySQL |
REST APIs over a normalized relational schema with a query-optimized backend. |
| 🚚 ZeroMile — 1st Prize, InnoTech Fest | Logistics Team Leadership |
Led a team to design a marketplace matching shippers with trucks on return routes, cutting empty trips and costs. Repo |
| Certification | Issuer | Level |
|---|---|---|
| AWS Certified Data Engineer – Associate (DEA-C01) | Amazon Web Services | Associate |
| AWS Certified Cloud Practitioner (CLF-C02) | Amazon Web Services | Foundational |
| Data Analytics Job Simulation | Deloitte × Forage | Simulation |
| Machine Learning Foundations | AWS Academy | Foundational |
| AI for Everyone | DeepLearning.AI | Foundational |
Data Engineering & Warehousing
Cloud
Languages & Data
AI / LLM
Backend & Tools
- Medallion pipeline with Snowflake, dbt and Airflow
- AWS Certified Data Engineer – Associate
- LLM layer on a real warehouse (RAG + NL→SQL)
- First contributions merged into Apache Airflow
- Keep contributing upstream — deeper core / provider work
- Apache Spark / PySpark for large-scale processing
- dbt CI/CD (slim CI, state-based runs, automated docs)
- System design for data platforms (streaming, lakehouse patterns)
Open to Data Engineering, Data Analyst and Cloud internships, and to collaborating on pipelines, warehouses or AI-augmented analytics. Happy to talk AWS, dbt, Airflow, Snowflake, or anything data.
Turning raw, messy data into pipelines people can trust.