I am Darshil Mangukiya, a Computer Engineering student based in Fullerton, California, focused on data analytics, business analysis, BI development, and data engineering. I build production-style portfolio projects that transform raw data into reliable pipelines, governed KPI layers, executive dashboards, and business-ready insights.
SQL · Python · Power BI · Airflow · dbt · AWS · GCP · Azure · Databricks · Snowflake
Timeline
JAN 2024 – MAY 2026
M.S. Computer Science
California State University, Fullerton
JUN 2022 – DEC 2023
Data Analyst
Trexity Technologies
JAN 2022 – APR 2022
Software Development Intern
Universe Technologies
AUG 2018 – DEC 2023
E-Commerce Data Analyst (Part-Time)
Shivam Enterprise
JUN 2018 – JUN 2022
B.E. Computer Engineering
Gujarat Technological University
Project Index
Multi-marketplace e-commerce analytics across five marketplaces, backed by a governed Azure SQL warehouse and a Microsoft Fabric Delta lakehouse, with a 9-page Streamlit dashboard and an 8-page Power BI report covering fee, refund, revenue-quality, and margin-risk analysis.
Customer intelligence and product analytics platform using SQL, Python, PostgreSQL, and scikit-learn to analyze churn, CLV, cohorts, and segmentation, with a statistically rigorous A/B retention experiment cross-validated against an independent R analysis, plus FastAPI, Streamlit, and Excel reporting.
Multi-source marketing ETL and analytics warehouse with Python, Airflow, and dbt, including a live BigQuery/GCP pipeline ingesting this site's own GA4 data alongside synthetic ad and CRM sources, with attribution modeling, data quality gates, and Power BI/Streamlit reporting.
Customer 360 data platform with real Debezium/Kafka change-data-capture, identity resolution, dbt models validated across PostgreSQL and Snowflake with zero-mismatch parity checks, and privacy-safe reverse ETL activation.
Azure lakehouse reliability platform with a governed Bronze/Silver/Gold Delta pipeline, validated through a real Azure Databricks Serverless run that wrote data to ADLS Gen2 via Unity Catalog, orchestrated by Airflow with 13 fail-closed release gates and dbt/Power BI reporting.
Event-driven, multi-tenant data platform with FastAPI microservices, Kafka pipelines, PostgreSQL row-level-security tenant isolation, Spark Structured Streaming, Airflow orchestration, and Kubernetes-validated deployment manifests, backed by 460+ passing tests.
Multi-marketplace e-commerce analytics across five marketplaces, backed by a governed Azure SQL warehouse and a Microsoft Fabric Delta lakehouse, with a 9-page Streamlit dashboard and an 8-page Power BI report covering fee, refund, revenue-quality, and margin-risk analysis.
Customer intelligence and product analytics platform using SQL, Python, PostgreSQL, and scikit-learn to analyze churn, CLV, cohorts, and segmentation, with a statistically rigorous A/B retention experiment cross-validated against an independent R analysis, plus FastAPI, Streamlit, and Excel reporting.
Multi-source marketing ETL and analytics warehouse with Python, Airflow, and dbt, including a live BigQuery/GCP pipeline ingesting this site's own GA4 data alongside synthetic ad and CRM sources, with attribution modeling, data quality gates, and Power BI/Streamlit reporting.
Customer 360 data platform with real Debezium/Kafka change-data-capture, identity resolution, dbt models validated across PostgreSQL and Snowflake with zero-mismatch parity checks, and privacy-safe reverse ETL activation.
Azure lakehouse reliability platform with a governed Bronze/Silver/Gold Delta pipeline, validated through a real Azure Databricks Serverless run that wrote data to ADLS Gen2 via Unity Catalog, orchestrated by Airflow with 13 fail-closed release gates and dbt/Power BI reporting.
Event-driven, multi-tenant data platform with FastAPI microservices, Kafka pipelines, PostgreSQL row-level-security tenant isolation, Spark Structured Streaming, Airflow orchestration, and Kubernetes-validated deployment manifests, backed by 460+ passing tests.