I build practical data engineering projects, SQL investigation playbooks, and real-world analytics examples to help students, freshers, and aspiring data engineers understand how data issues are solved in real business environments.
- 💼 Data Engineer with experience in marketing analytics, cloud data platforms, SQL validation, and dashboard investigation.
- ☁️ Working with tools like BigQuery, GCP, Azure Data Factory, Azure Synapse, Databricks, and Power BI.
- 📊 Strong focus on real-world data quality checks, source vs dashboard mismatch analysis, attribution logic, and reporting validation.
- 🧠 Currently learning AI, ML, AI agents, and automation workflows to combine data engineering with intelligent systems.
- 📚 Creating beginner-friendly GitHub repositories that explain practical data engineering issues step by step.
My GitHub repositories are mainly focused on helping learners understand real-world data engineering scenarios, including:
- 🔍 Dashboard vs source data mismatch investigations
- 📁 Campaign data validation using SQL and BigQuery
- 🛠️ Data engineering issue playbooks
- ☁️ Azure and GCP data pipeline examples
- 📊 Marketing analytics and attribution logic
- 🤖 AI-powered data investigation and automation ideas
| Repository | Purpose |
|---|---|
| Dashboard vs Source Data Mismatch | Step-by-step guide to investigate why dashboard numbers do not match source data. |
| Real-World Data Engineering Issue Playbook | A practical collection of common data issues, root causes, SQL checks, and fixes. |
| Campaign Data Validation with BigQuery | Beginner-friendly marketing analytics validation project using sample datasets. |
| Data Issue Investigation Report Generator | A tool idea to generate structured investigation reports from data quality findings. |
- SQL and BigQuery data validation
- Marketing analytics data pipelines
- Dashboard vs source data mismatch investigation
- Azure Data Factory, Synapse, Databricks, and cloud data engineering
- Power BI and Looker Studio reporting workflows
- Data modeling, star schema, snowflake schema, and warehouse design
- AI and automation ideas for data engineers
