About Me
Data Engineer with 1 year of hands-on experience designing and delivering batch and streaming data pipelines, modern Lakehouse platforms, and business intelligence solutions. Strong expertise in Python, SQL, PySpark, Apa…
Data Engineer with 1 year of hands-on experience designing and delivering batch and streaming data pipelines, modern Lakehouse platforms, and business intelligence solutions. Strong expertise in Python, SQL, PySpark, Apache Kafka, Airflow, and Apache Iceberg, applying Medallion Architecture, Data Quality standards, and Star Schema modeling to convert raw enterprise data into analytics-ready datasets. Proven track record in executing freelance end-to-end data pipelines from ingestion design through Gold-layer data marts.
Experience
Part-Time Python & Coding Instructor
<p>Teach project-based Python, algorithms, and software development fundamentals through practical, hands-on exercises.</p><p> Mentor students 1:1 on code optimization, debugging, and software design principles.</p>
Freelance Data Engineer
<p>Built end-to-end batch data pipelines on Microsoft Fabric, ingesting multi-source data with Spark into a Delta Lakehouse.</p><p> Implemented Bronze, Silver, and Gold layers with reusable Spark transformations, schema validation, data quality rules, and rejected-record handling.</p><p> Developed modular analytical models with dbt using SQL/Jinja, incremental models, data tests, and model dependencies.</p><p> Designed analytical star schemas with fact and dimension tables, applying SCD Type 2 for historical data tracking.</p>
Business Intelligence Analyst (Internship)
<p>Developed interactive Power BI dashboards tracking patient recovery and satisfaction metrics, giving operational leaders real-time visibility.</p><p> Automated recurring reporting workflows with Airflow, cutting manual spreadsheet handling by 30%.</p>
PROJECTS
Enterprise Data + AI Platform Architecture (DataMind AI)
<p>This repository contains enterprise-grade architecture documentation for a modern Data + AI platform designed for millions of records/day across multiple business domains:</p><ul><li>Support Tickets (customer support operations)</li><li>Payments (financial transactions, fraud signals, settlement)</li><li>Telecom CDRs (call detail records / network usage events)</li></ul><p>The platform's target architecture is designed to deliver:</p><ul><li>Trusted analytics (lakehouse + warehouse) [Implemented]</li><li>Operational reporting and APIs [Implemented]</li><li>Machine learning at scale (fraud, churn, classification, anomaly detection) [WIP / Planned]</li><li>GenAI experiences (Text-to-SQL, RAG, agentic workflows) with robust governance and security [Partially Implemented]</li></ul><p></p>