Wealthsimple - Sr Software Developer, Privacy Engineering

  

Designing and building a centralized data access governance platform that enables secure, self-service access to Snowflake while enforcing least-privilege principles and protecting sensitive information.

  • Access Governance & Automation: Developing a self-service permissions platform with automated approval workflows, intelligent grant bundling based on dashboards and query history, role provisioning, and revocation of unused access.
  • Privacy & Security Engineering: Implementing fine-grained role-based access controls (RBAC), dynamic data masking policies, and multi-level approval workflows for sensitive PII, ensuring access is granted only when needed and for its intended purpose.
  • Platform Architecture & Modernization: Owning the Satori integration and driving its replacement with an internally developed access governance solution, consolidating permission management, policy enforcement, and access lifecycle automation.
  • Cross-Functional Technical Leadership: Partnering with engineering and business domains to establish least-privilege access models, align team-based permissions, and support a secure migration from Amazon Redshift to Snowflake.
  • Cybersecurity Innovation: Contributing to the development of a Cyber Reasoning System to advance security analysis and automation capabilities.

Prodigy Education - Senior Data Engineer

Improving the reliability of Prodigy’s data pipelines and data lakehouse.

• Currently embedded in a product team working to expose modelled data to users
• Worked across teams to build and scale an event pipeline to ingest thousands of messages per second.
• Developed processes for deploying ml pipelines using MLflow, implemented PII redaction, and added automation tools
• Mentoring, training and on-boarding new teammates.
• Expanding my understanding of data systems, reliability, data warehousing/data lakes

Technologies: DBT, SQL, Python, Spark, AWS, Databricks, Docker, Airflow, Terraform, Datadog, Kubernetes

Skills Developed :
Data pipeline scheduling and automation
DBT model development and optimization
Automating backfill processes
Updating and testing packages
Developing production ML pipeline processes

Shopify Data Platform Engineer

 


Member of the Starscream Runtime - Batch Transformations team, maintaining, scaling and upgrading Shopify’s data ETL platform.

  • Currently adding tools to assist in the migration of 3000+ batch transformation flows from Apache Oozie to Airflow. 
  • Lead the migration of 3000+ batch transformation flows from unmanaged Hadoop YARN to Google's Dataproc and coordinating with data science teams. Updated coordinator tools to ensure a smooth and seamless transition for our data scientists.
  • Helped to convert the core part of the platform to be python 2 and python 3 compatible.
  • Mentoring, training and on-boarding new teammates.
  • Expanding my understanding of data systems, reliability, data warehousing/data lakes
  • Technologies: Python, Spark, Hadoop, GCP, Dataproc, Docker, Oozie, Airflow, Terraform, Datadog, SQL, Kubernetes
  • Skills Developed :
    • Data pipeline scheduling and automation
    • Continuous deployment pipeline maintenance
    • Troubleshooting and mitigating incidents involving data corruption
    • Refactoring and updating legacy code
    • Test-driven software development

Lead Engineer

 
  
Technologies: Node.js, React.js, Mongodb, RESTful API
Major Challenges:
  • Designing a fast, clean and responsive platform for users to easily and enjoyably work on
  • Adding a RESTful API for integration with the Zymewire platform
  • Scaling the app to allow for multiple users to simultaneously be working on the same task
  • Auto-accepting submitted tasks when the content was similar enough for what we needed.

Data Team Lead, Engineer, Developer Data

Over the 4 years, I wore many hats, but I'm most proud of establishing, growing and managing the data team that was responsible for building, maintaining and scaling the company’s data pipelines.
  • Major challenges :
    • seeking out new sources of data for finding and categorizing companies
    • managing how we tracked 4000+ companies in their daily activities, scraping the latest news, seeking out their future plans to start clinical trials, attend conferences, hire new talent, release results, apply for funding, etc
    • designing data models and pipeline processes for the acquisition of all the above collected data
    • automating the processes to reduce the need for human intervention and review
    • creating machine learning models to assist in the categorization process
  • Technologies: Ruby, Ruby on Rails, React.js, Javascript, Mongodb
  • Skills Developed :
    • test-driven software development, with weekly code reviews
    • extracting, transforming and loading (ETL) large datasets
    • designing and automating the loading of new datasets
    • defining metrics to help the team stay focused on projects aligned with the business
    • experimenting with processes to help improve the team’s workflow
    • growing a team
    • managing team member’s personal growthT