Available for work · Toronto, ON

I engineer data into intelligent systems

// Data · AI · Machine Learning · Cloud

I'm a Data & ML engineer with 3+ years turning raw, messy data into scalable pipelines, production ready models, and cloud native architecture, bridging the gap between engineering and data science.

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0: Years of experience
0: Shipped projects
0: Certifications
0: AWS · Azure · GCP

01 Toolbox

Technologies I work with

A complete data toolkit, from ingestion and orchestration through modeling, GenAI, and deployment.

Languages & Query

Python
SQL
Scala
TypeScript
Java
C++

Data Engineering

Spark
PySpark
Kafka
Airflow
Hadoop
Hive
Flink

Cloud & Warehousing

AWS
Azure
GCP
Databricks
Snowflake
Redshift
BigQuery

ML & Deep Learning

PyTorch
TensorFlow
Keras
Scikit-Learn
XGBoost
CNN · RNN · LSTM

GenAI & LLMs

LLMs
RAG Pipelines
Agentic AI
LangGraph
Transformers
Prompt Engineering

MLOps & DevOps

Docker
Kubernetes
Terraform
MLflow
GitHub Actions
CI/CD

Analytics & BI

Power BI
Tableau
Looker
Grafana
Pandas
NumPy

Automation & Platform

Power Automate
Copilot Studio
Jira
SharePoint

02 Experience

Where I've made an impact

Associate · Data & AI
Sep 2025 — Present

PwC Canada

Modernizing a Tier 1 Canadian bank's management reporting platform: migrating legacy Informatica ETL to a cloud ready AWS architecture on Redshift and Spark, and shipping governed GenAI solutions on Azure.
- Designed a 3 layer data architecture with end to end Airflow DAGs, PySpark transformations, PII masking, and data quality checks
- Cut manual migration effort by ~98% with an LLM powered accelerator generating SQL, DDLs, and source to target mappings
- Built a GenAI reporting agent on Azure AI Foundry, saving 17+ managers 10+ hrs/week
Machine Learning Engineer
Jan 2022 — Dec 2022

BrainyBeam Technologies

Owned end to end ML pipelines, from data cleaning and feature engineering to experiment tracking and containerized deployment, for production models.
- Shipped a telecom churn model (XGBoost, MLflow, Dockerized Flask) reaching 0.87 AUC ROC with GitHub Actions CI/CD
- Cut deployment latency by 40% and improved training efficiency by 25%
- Engineered 18+ features, reducing overfitting by 30%
Data Analyst
Jun 2021 — Nov 2021

Ecubix

Directed SQL based ETL workflows and analytics on high volume datasets, applying advanced statistical methods to uncover trends, detect anomalies, and support evidence based planning.
- Drove a 20% increase in customer acquisition through actionable insights
- Enabled a 15% revenue boost via timely, data driven interventions
Python Developer Intern
Jan 2020 — Dec 2020

Bascom Bridge Education

Developed automation scripts for high volume data processing, optimizing Python solutions for complex workflows.
- Reduced operational overhead by 32% through automation
- Accelerated project delivery by 10%

03 Selected work

Projects

End to end data engineering pipelines and applied machine learning, with the metrics that mattered.

Data Engineering+50% efficiency

Real Time Stock Market Streaming

Real time financial streaming pipeline on Kafka and AWS (EC2, S3, Glue, Athena), boosting analysis efficiency by 50% on high throughput market data.

Kafka
AWS
Glue
Athena

Data Engineering+50% efficiency

Football Analytics Pipeline

End to end analytics pipeline on Apache Airflow and Azure Data Lake, automating extraction, cleaning, and transformation with Databricks and Power BI.

Airflow
Azure Data Lake
Databricks
Power BI

Data Engineering+60% efficiency

Uber Trip Analytics

Streamlined ETL and analytics on GCP with BigQuery, Mage, and Looker Studio, delivering insight into trip patterns and fare distribution.

GCP
Mage
BigQuery
Looker

Data Engineering+40% throughput

Reddit Data Engineering Pipeline

Scalable ETL on AWS (S3, Glue, Athena, Redshift) orchestrated with Airflow, boosting data processing efficiency by 40%.

Airflow
AWS
Redshift
PostgreSQL

GenAIAgentic RAG

GenAI Agentic Customer Support

Multi agent RAG system on GCP using LangGraph with supervisor orchestration and full observability across the agent workflow.

LangGraph
Vertex AI
GCP
Docker

Machine Learning95% accuracy

Cell Segmentation with YOLOv8

95% accurate cell segmentation system on YOLOv8 and Azure, with a Docker and GitHub Actions CI/CD pipeline that cut deployment time by 40% for healthcare diagnostics.