"I spent 14 months keeping Microsoft's Azure SQL databases alive in production at HCL Technologies. Now I'm building the data pipelines and warehouses behind them."
I'm a B.Tech graduate (2022) with a background that runs through enterprise Microsoft support → deliberate cloud engineering pivot → live 2026 portfolio sprint.
While most engineers learn in sandboxes, I was diagnosing critical production SQL deadlocks, performance bottlenecks, and high-priority escalations as an Azure SQL DB Technical Support Engineer at HCL Technologies — with Microsoft as the direct client.
In January 2024, I made a calculated decision: go deep into Azure Data Engineering. I call the 26-month period that followed my "Advanced Cloud Residency".
Today I'm applying for Data Analyst and Azure Data Specialist roles simultaneously — and actively committing to GitHub every week.
| Status | Project | Stack | Repo |
|---|---|---|---|
| ● LIVE | SQL Data Warehouse — Medallion Architecture | Azure Synapse · PySpark · Bronze/Silver/Gold | → View |
| ● LIVE | ADF Pipeline System — Incremental Loads | Azure Data Factory · Parent-Child Pipelines | → View |
| ⚡ Next | Power BI Dashboard — Advanced DAX | Power BI · DAX · Data Modeling | Coming soon |
Oct 2022 ─────── Dec 2023 Jan 2024 ────────────── Feb 2026 March 2026 → Now
│ │ │
HCL Technologies Advanced Cloud Active Sprint
Microsoft Client Residency DA + ADE Roles
Azure SQL DB ADF · Databricks Applying Now
Tech Support Eng. Synapse · PySpark GitHub: Active
│ Medallion Arch. │
└───────────────────────────────────────────────────────────────────────┘
Every step intentional. Every commit deliberate.
| Tool | Proficiency |
|---|---|
| Azure Data Factory | ██████████░ 85% |
| Azure Databricks | █████████░░ 80% |
| PySpark | ████████░░░ 78% |
| Azure Synapse Analytics | ███████░░░░ 75% |
| Medallion Architecture | ██████████░ 85% |
| Incremental Load + Parent-Child Patterns | █████████░░ 83% |
Cloud & Compute
BI & Visualization
Languages & Databases
|
Enterprise-grade incremental load pipelines with Parent-Child orchestration. Schema drift handling, retry logic, parameterized ingestion. Stack:
|
End-to-end DW from scratch. Bronze (raw) → Silver (clean) → Gold (analytics-ready). Full transformation layer. Stack:
|
|
End-to-end retail pipeline. 2GB+ dataset, Python + SQLAlchemy, statistical hypothesis testing, Power BI dashboard. Stack: |
Full EDA revealing pricing patterns, seasonality, and neighborhood intelligence. 15+ view Tableau dashboard. Stack: |
From production SQL support at Microsoft to engineering the data pipelines behind enterprise decisions. Every month of the "residency" was a deposit. March 2026 is the withdrawal.