Data Engineers in Toronto

Data Engineers in Toronto June 2026 Semimonthly Meeting

Topic: Data Mesh as the Foundation for AI/ML in Financial Services

Abstract:
Financial institutions want AI/ML at scale, but brittle data pipelines, silos, and compliance demands slow progress. This talk shows how a Data Mesh—domain-oriented ownership, data-as-product, self-serve platforms, and federated governance—becomes the foundation for reliable, reusable ML features and trustworthy models. We’ll map mesh principles to FS use cases—fraud detection, risk, personalization—and show patterns for feature stores, lineage, quality, and access controls that satisfy regulators while accelerating delivery. Attendees will get a pragmatic blueprint: where to start, how to sequence capabilities, metrics that prove value, and pitfalls to avoid on the road from pilots to production.

Speaker: Santosh Durgam, Data Engineering & Analytics Leader

Speaker Profile:
Santosh Durgam is a data engineering & analytics leader with 20+ years building governed, high-scale data platforms across retirement/401(k), broader financial services, and healthcare. He leads cross-functional teams that deliver production-grade data lakes, lineage-aware pipelines, and ML-enabled analytics on cloud—translating governance into measurable business outcomes.

Recent speaking includes SQL Saturday Minnesota 2025, where he presented “From Ingestion to Insights: Building Robust Data Pipelines in AWS” to an in-person community audience. He has also contributed to international research forums and science conferences, and is invited to speak at ICDPN-2025 (International Conference on Data Processing & Networking), engaging practitioners and scholars on data engineering, governance, and analytics at scale. Santosh actively publishes/curates work via Google Scholar and shares practical playbooks for data quality, metadata/lineage, and operating models that connect data platforms to financial decisioning.

Beyond delivery, Santosh serves the community as a peer reviewer of scholarly work on data/ML methodologies and as a judge/mentor for select industry and academic competitions, reinforcing peer validation and public recognition. He champions modern data culture—mentoring engineers and product leaders, and advocating automation (incl. AI agents) to elevate reliability, speed, and auditability in regulated environments. Santosh recently completed his Executive MBA, sharpening strategy and value-creation at the intersection of data, risk, and growth

Data Engineers in Toronto July 2026 Semimonthly Meeting

Topic: Introduction to PySpark in Microsoft Fabric

Abstract:
With all of the engineering features in Microsoft Fabric, which medium should you use to move and transform data? Low-code data flows and pipelines? Good old relational SQL? What about this newfangled PySpark everyone is buzzing about?

If the last option piques your curiosity and you haven't tried it, this is the session for you. I'll cover basic Python principles that will make even complicated Python easy to read. Then I will explain important topics to understand when managing your Spark environment. Finally, I'll showcase Fabric features and community content that can support your next steps in learning to implement PySpark in Fabric.

Speaker: Jared Kuehn, Data Engineer

Speaker Profile:
For over a decade, Jared has been a data engineering consultant implementing Microsoft products. For more than three decades, he has been honing his skills in theater and other performing arts. As a speaker, Jared marries these two disciplines together, creating dynamic presentations that add entertainment to education. This symbiotic relationship can improve presentation engagement, support attendees in knowledge retention, and foster a culture of passion for the data industry.

As a speaker, Jared has spoken at events such as:
-Fabcon Vegas (Microsoft Fabric Community Conference)
-DataCon Seattle (Microsoft Data Conference)
-PASS Summit
-SQL Saturdays, Multiple
-Microsoft Fabric Global Online Conference
-Future Data Driven Summit
-GroupBy Conference
-and more!

He also runs the YouTube channel DataBard, focused on making Data fun and teaching techniques along the way.

Technically-speaking, Jared has multiple Microsoft certifications in both on-prem and cloud technologies. He has extensive knowledge in:
-Microsoft Fabric
-SQL Query Development and Performance tuning
-Kimball Data Modeling
-ETL design patterns
-Azure SQL DB and Azure SQL MI

In his spare time, he continues to perform in community theater productions, as well as musically for his church. Upon request, he would be happy to assist with more theatrical portions of events, such as performing musical numbers.

Data Engineers in Toronto August 2026 Semimonthly Meeting

Topic: Running GitHub Actions Offline: Debug CI/CD workflows right from your local machine

Abstract:
Ever wanted to try out your GitHub Actions without waiting for the cloud to spin up the runners? Well, you can! Testing GitHub Actions locally lets you build, test, and debug your CI/CD workflows right from your machine. Through a tool such as act, you can simulate GitHub’s environment for your workflows locally using Docker. This means no more pushes of dozens of commits just to see if your syntax in the YAML file is wrong. You can make changes, execute, and validate your automation as many times as you want, even on a plane where there's no Wi-Fi. Just install Docker, install act, load your secrets locally, and run commands like act push to test your events in the workflows. That's faster, lightweight, and the greatest productivity booster. Taking GitHub Actions offline is not about isolation; it's about freedom and control over your automation pipeline.

Speaker: Steve Yonkeu, Software Engineer & Microsoft MVP

Speaker Profile:
Steve Yonkeu is a backend software engineer dedicated to delivering excellence in architecture, performance, and modularity. For over 5 years he has been leading teams and projects and open source communities worldwide. Steve is also the founder of Django Cameroon and Python Cameroon communities today. He is also an organizer at PyCon Africa and speaker at PyConUS.

Data Engineers in Toronto September 2026 Semimonthly Meeting

Topic: Building Collaborative AI Agents Using AI Foundry Agent Service

Abstract:
As enterprise AI adoption grows, many real-world scenarios can no longer be solved by a single conversational agent. Instead, they require multiple specialized agents that collaborate, share context, and delegate responsibilities intelligently. This session focuses on how to design and implement multi-agent architectures using Azure AI Foundry’s Agent Service.

We’ll start by breaking down when and why multi-agent systems make sense, then walk through a practical scenario where agents are assigned clear roles such as data retrieval, reasoning, and action execution. Using AI Foundry Agent Service, you’ll see how these agents are created, connected, and orchestrated to work together while maintaining context and control.

Rather than focusing on theory, the session emphasizes practical design patterns, architecture decisions, and implementation considerations, including agent boundaries, communication flows, and scaling agent-based solutions safely in enterprise environments.

By the end of the session, attendees will have a solid understanding of how to move from a single-agent approach to a collaborative, multi-agent model and how to apply these patterns using AI Foundry in their own solutions.

Key Takeaways:
- Understand when multi-agent architectures are the right choice
- Learn how to design role-based agents using AI Foundry Agent Service
- Explore real-world coordination and orchestration patterns
- Gain practical guidance for scaling and governing multi-agent systems
- Leave with a reusable architecture blueprint for enterprise AI agents

Speaker: Mitul Tailor, Snr. Data & AI Engineer

Speaker Profile:
am a Senior Data & AI Engineer at Long View Systems, specializing in Azure services, data engineering, and AI-driven solutions. With expertise in Azure Data Factory, Fabric, Copilot Studio, and data migration, I have successfully delivered scalable and efficient data solutions.

I hold a Post Graduate Certificate in Generative AI, a PG Diploma in ML & AI, and a Bachelor's in Computer Science. I am DP-600 & AI-102 certified, demonstrating my expertise in Microsoft Azure Enterprise Data Analyst solutions. Additionally, I have a strong understanding of Retrieval-Augmented Generation (RAG) AI and Azure AI Foundry, exploring how these technologies can be leveraged for intelligent automation and data-driven insights.

Recognized by clients for my clear and precise development work, I am passionate about automation, AI, and robotics. Outside of work, I love to travel and have a deep interest in cars.