Brian is available for hire
Hire BrianBrian Jin
Verified Expert in Engineering
Data Architect and Developer
Toronto, ON, Canada
Toptal member since June 18, 2020
Bio
Brian has a decade of substantial experience in data integration, data architecting, and data modeling in various industries such as government, banking, investment, and so on. The way Brian works is by designing the most optimized, scalable, and robust solution based on requirements. Brian's curiosity is what drives him to learn about new business areas, tackle new challenges, and embrace new technologies.
Portfolio
AB-InBev - AB Inbev (USA)
Data Mesh, Data Management Platforms, Databricks, Azure Databricks, Snowflake...
Toronto Public Library
MDM, SQL Server Reporting Services (SSRS), Microsoft Power BI, Machine Learning...
ObjectSharp Consulting
SQL Server 2008 R2, SQL, Azure, Big Data Architecture, Cloud Architecture...
Experience
- Database Modeling - 13 years
- Dimensional Modeling - 13 years
- Data Visualization - 13 years
- Data Modeling - 13 years
- Data Warehousing - 12 years
- Data Architecture - 9 years
- Big Data Architecture - 7 years
- Cloud Architecture - 7 years
Availability
Part-time
Preferred Environment
Azure Data Lake, Microsoft Power BI, Python, Microsoft SQL Server, Azure
The most amazing...
...project I've led and completed was an Azure IoT project and subsequently won Microsoft IMPACT Award in 2015.
Work Experience
System Architect
2020 - 2023
AB-InBev - AB Inbev (USA)
- Led the design and oversaw the data operation at BEES, including data infrastructure management, security management, and access management to enable different data domains to achieve excellence in data engineering and data analytics.
- Managed various POC projects with vendors to achieve operational and financial efficiency for the enterprise data platform.
- Supported and guided data engineer leads and data analytics leads to achieving optimization and continuous improvements in data operation.
- Identified the operational deficiencies between data analytics and data engineering and introduced the concept of data modeling, specifically business intelligence, which allowed the analytics to write more efficient analytical queries.
- Designed and managed the implementation of the distributed data architecture in 15+ countries and 20+ data domains in three years.
Technologies: Data Mesh, Data Management Platforms, Databricks, Azure Databricks, Snowflake, Cloud Infrastructure, Azure DevOps, Data Engineering, Data Lakes, Data Analytics, ETL, Database Modeling, Data Modeling, Data Visualization, Data Warehouse Design, Data Warehousing, Azure Data Lake, Microsoft Power BI, Azure, SQL, Agile Software Development, Python, Machine Learning, Microsoft SQL Server, Streaming Data, MDM, Source Control Management, Stream Processing, MongoDB, Cloud Architecture, Data Migration, Database Architecture, Microsoft Azure, Microsoft Azure Cloud Server, Azure SQL Data Warehouse, Dedicated SQL Pool (formerly SQL DW), Azure Synapse, APIs, Azure Data Factory (ADF), Data Pipelines, Leadership, Data Analysis, ETL Tools, Database Lifecycle Management (DLM), ETL Pipelines, Big Data, Cloud, Microsoft Excel, JSON, Dashboards, Business Intelligence (BI), Data, ELT, Real-time Data, Apache Kafka, Docker, Kubernetes, REST APIs, Unstructured Data Analysis, Pipelines
Azure Data Architect
2018 - 2020
Toronto Public Library
- Assessed the business, data, and reporting requirements. Created several architectural recommendations and developed the most cost-effective but performing and future-proven data platform solution.
- Developed several data pipeline approaches using ADFv2, like copy, data flow, and Databricks Notebooks using Python. Recommended the best solution based on the requirements, including cost.
- Conducted research on data modernization strategy and recommended the data modernization roadmap.
- Participated in organizational master data strategy and provided and recommended different approaches with help from Gartner.
- Contributed to procurement, policy review, and other business-related meetings to provide data governance advice.
- Created several organizational dashboards and reports using Power BI and SSRS reporting.
Technologies: MDM, SQL Server Reporting Services (SSRS), Microsoft Power BI, Machine Learning, Python, SQL, Data Warehouse Design, Data Warehousing, Databricks, Azure, Cloud Architecture, Database Architecture, Microsoft Azure, Data Architecture, Data Engineering, Data Lakes, Data Analytics, ETL, Database Modeling, Data Modeling, Data Visualization, Azure Data Lake, Agile Software Development, Microsoft SQL Server, Source Control Management, Data Migration, Microsoft Azure Cloud Server, Dedicated SQL Pool (formerly SQL DW), Azure SQL Data Warehouse, Azure Databricks, Cloud Infrastructure, APIs, Azure Data Factory (ADF), Data Pipelines, Leadership, Data Analysis, ETL Tools, Database Lifecycle Management (DLM), ETL Pipelines, Big Data, Cloud, Microsoft Excel, T-SQL (Transact-SQL), JSON, Dashboards, Business Intelligence (BI), Data, ELT, REST APIs, Unstructured Data Analysis, Pipelines
Azure Data Consultant
2018 - 2018
ObjectSharp Consulting
- Worked with the Microsoft technical sales team to create side-by-side feature comparisons between Azure SQL managed instances and SQL Server 2008 R2 on premise.
- Worked on detailed features including indexes, replications, SSRS, SSIS, SSAS, job agent, and so on.
- Signed a migration project from a financing firm successfully.
Technologies: SQL Server 2008 R2, SQL, Azure, Big Data Architecture, Cloud Architecture, Microsoft Azure, Data Engineering, Data Analytics, ETL, Database Modeling, Data Modeling, Data Visualization, Data Warehouse Design, Data Warehousing, Microsoft Power BI, Agile Software Development, Microsoft SQL Server, Source Control Management, Data Migration, Azure Data Factory (ADF), Data Pipelines, Data Analysis, ETL Tools, Database Lifecycle Management (DLM), ETL Pipelines, Cloud, T-SQL (Transact-SQL), JSON, Business Intelligence (BI), Data, ELT, Unstructured Data Analysis
Database Consultant
2018 - 2018
Gluskin Sheff Associates
- Migrated a financial database for a trading analyst from MySQL to SQL Server 2016.
- Converted 20+ Excel applications written in VB and Python to use SQL Server 2016 due to syntax changes.
- Refined and optimized some applications and the new SQL Server to achieve a high performance.
- Provided technical training to business analysts on SQL Server.
- Advised and designed the future proven Azure database platform as an enterprise data strategy.
Technologies: Visual Basic, Python, SQL Server 2016, MySQL, Data Migration, Data Engineering, Data Analytics, ETL, Database Modeling, Data Modeling, Data Visualization, Data Warehouse Design, Data Warehousing, Microsoft Power BI, SQL, Microsoft SQL Server, ETL Tools, T-SQL (Transact-SQL), JSON, Business Intelligence (BI), Data, ELT, Pipelines
Business Intelligence Consultant
2017 - 2018
TD Bank Technology Solution
- Implemented transnational replication to support OLTP transactions and real-time reporting.
- Created a dimensional data model using a star schema for data analytics.
- Implemented Power BI for performance scorecards and SSRS reports for scheduled reporting.
- Trained junior team members and participated in performance reviews.
Technologies: Dimensional Modeling, Microsoft Power BI, SQL Server Integration Services (SSIS), SQL Server Reporting Services (SSRS), Database Architecture, Data Engineering, Data Analytics, ETL, Database Modeling, Data Modeling, Data Visualization, SQL Server 2014, SQL Server 2012, SQL Server 2008 R2, Data Warehouse Design, Data Warehousing, SQL, Agile Software Development, C#, Microsoft SQL Server, Accounting, Data Pipelines, Data Analysis, ETL Tools, Database Lifecycle Management (DLM), ETL Pipelines, Microsoft Excel, T-SQL (Transact-SQL), JSON, Business Intelligence (BI), Data, ELT, REST APIs, Unstructured Data Analysis, Pipelines
Business Intelligence Consultant
2010 - 2017
Various Full-time Positions
- Developed various database and data platform solutions for TD Bank Fraud, Dream REIT, Brookfield REIT, RIO CAN REIT, Carlsberg Sales, Gluskin & Sheff Investment, and more.
- Performed various pre-sale projects with Microsoft and consulting firms.
- Started the Azure platform at an early stage for Proof-of-Concept, including on-premise to cloud migration and on-premise to cloud feature comparison research.
Technologies: Oracle, MySQL, Dimensional Modeling, C#, SSAS, SQL Server Reporting Services (SSRS), SQL Server Integration Services (SSIS), Tableau, Microsoft Power BI, Python, SQL, Azure, Database Architecture, Microsoft Azure, Microsoft Azure Cloud Server, Azure SQL Data Warehouse, Dedicated SQL Pool (formerly SQL DW), Azure Synapse, Data Engineering, Data Analytics, ETL, Database Modeling, Data Modeling, Data Visualization, SQL Server 2014, SQL Server 2012, SQL Server 2008 R2, Data Warehouse Design, Data Warehousing, Agile Software Development, Microsoft SQL Server, Accounting, APIs, Azure Data Factory (ADF), Data Pipelines, SAP, SQL Server Analysis Services (SSAS), Data Analysis, ETL Tools, Database Lifecycle Management (DLM), ETL Pipelines, Big Data, eCommerce, Microsoft Excel, T-SQL (Transact-SQL), JSON, MIPS, XML, HL7 FHIR Standard, Amazon Web Services (AWS), ELT, Docker, REST APIs, Unstructured Data Analysis, Pipelines, Hospitality
Experience
System Architect
I led the design and oversaw the data operation at BEES, including data infrastructure management, security management, and access management to enable different data domains to achieve excellence in data engineering and data analytics. I managed various POC projects with vendors to achieve operational and financial efficiency for the enterprise data platform. I also supported and guided data engineer leads and data analytics leads to achieve optimization and continuous improvements in data operation.
My work also included identifying the operational deficiencies between data analytics and data engineering and introducing the concept of data modeling, specifically business intelligence, which allowed the analytics to write more efficient analytical queries. Additionally, I designed and managed the implementation of the distributed data architecture in 15+ countries and 20+ data domains in three years.
My work also included identifying the operational deficiencies between data analytics and data engineering and introducing the concept of data modeling, specifically business intelligence, which allowed the analytics to write more efficient analytical queries. Additionally, I designed and managed the implementation of the distributed data architecture in 15+ countries and 20+ data domains in three years.
Design and Implementation of an Enterprise Data Warehouse for a Government Agency
As an Azure data architect, I successfully delivered an enterprise data warehouse design and implementation for a government agency using the Azure platform (ADF v2, Azure SQL, databricks, data lake, logic apps, automation runbooks, Power BI, and so on).
I participated in procurement, policy review, and other business-related meetings to provide data governance advice. I also converted several manual processes to automated ones and improved staff productivity.
I participated in procurement, policy review, and other business-related meetings to provide data governance advice. I also converted several manual processes to automated ones and improved staff productivity.
Azure IoT Hub for a Mining Company
I created an IoT hub pipeline that transferred data from IoT sensors deployed to train cabins. I stored the data using Azure Blob Storage and designed a Python application to clean up the data. Then I loaded it to the Azure SQL database for the daily dashboard to visualize the overall quality metrics. I collaborated with a team of data scientists and explored potential ML models to benefit quality control.
Consumer Segmentation for a Startup
I led and designed a consumer segmentation data model using massive firewall log data in collaboration with other members. I utilized many types of open-source software to minimize technology expenses during the proof-of-concept stage and built the transition plan for production deployment.
Data Integration Project for an Advertising Agency
I created a data pipeline to consolidate more than ten data sources on Azure platforms by using Azure Data Factory v1 and a Windows service application on Azure VM. The data included the Google Analytics API, Facebook Page API, Twitter API, Bing Ads API, Nielson viewership data, and more. I also created a data model for campaign analysis on Azure SQL and designed Power BI dashboards for daily campaign metrics.
Education
2005 - 2009
Bachelor's Degree in Computer Science
University of Waterloo - Waterloo, Ontario, Canada
Certifications
DECEMBER 2015 - PRESENT
MCSA SQL Server 2012
Microsoft
Skills
Libraries/APIs
REST APIs, PySpark
Tools
SSAS, Microsoft Power BI, Microsoft Excel, Tableau
Languages
Snowflake, SQL, Python, T-SQL (Transact-SQL), C#, XML, Visual Basic, Java, JavaScript, Octave, MIPS
Paradigms
Dimensional Modeling, Agile Software Development, ETL, Business Intelligence (BI), Azure DevOps, HL7 FHIR Standard
Platforms
Databricks, Azure, Azure SQL Data Warehouse, Dedicated SQL Pool (formerly SQL DW), Azure Synapse, Apache Kafka, Docker, Oracle, Amazon Web Services (AWS), Kubernetes
Storage
Microsoft SQL Server, MySQL, SQL Server 2016, SQL Server 2008 R2, SQL Server 2012, SQL Server 2014, SQL Server Integration Services (SSIS), SQL Server Reporting Services (SSRS), SQL Server Analysis Services (SSAS), SSAS Tabular, Database Architecture, Data Lakes, Database Modeling, Data Pipelines, Database Lifecycle Management (DLM), JSON, NoSQL, MongoDB, Azure Cosmos DB
Industry Expertise
Accounting
Frameworks
Data Lakehouse
Other
Azure Data Lake, Data Warehousing, Computer Science, Data Warehouse Design, Source Control Management, Data Modeling, Data Visualization, Big Data Architecture, Cloud Architecture, Data Migration, Microsoft Azure, Microsoft Azure Cloud Server, Data Architecture, Data Mesh, Data Management Platforms, Azure Databricks, Data Engineering, Data Analytics, APIs, Azure Data Factory (ADF), Data Analysis, ETL Tools, ETL Pipelines, Cloud, Dashboards, Dashboard Development, Reporting, Data, ELT, Unstructured Data Analysis, Pipelines, Hospitality, MDM, Stream Processing, Streaming Data, Cloud Infrastructure, Leadership, SAP, Big Data, eCommerce, Real-time Data, Machine Learning
Collaboration That Works
How to Work with Toptal
Toptal matches you directly with global industry experts from our network in hours—not weeks or months.
1
Share your needs
Discuss your requirements and refine your scope in a call with a Toptal domain expert.
2
Choose your talent
Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.
3
Start your risk-free talent trial
Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.
Top talent is in high demand.
Start hiring