Glenn Sawatsky

About Glenn Sawatsky

I build data platforms and API infrastructure that other teams depend on. The kind of systems where data quality, reliability, and clear contracts are not nice-to-haves but core product requirements.Most of my career has been at the intersection of complex data infrastructure and regulated industries. I have built Banking as a Service platforms from scratch, launched Credit Card as a Service products through third-party integration ecosystems, and currently own the data platform at System1 where the scope has expanded from pipeline engineering into AI-native tooling: agentic workflows, semantic layer design, LLM-powered data applications, and intelligent data systems.A few things that define how I work:I think in data models before I think in features. Formal conceptual modeling shapes how I approach platform design. Getting the underlying model right before specifying the API or the pipeline tends to prevent a lot of expensive rework downstream. Object Role Modeling is my preferred approach, though I am also deeply familiar with Entity Relationship Diagramming.I write specs that engineers can actually build from. In platform and API product work, ambiguous requirements create fragmentation. Working directly alongside engineering teams over many years has given me a clear sense of what \"done\" looks like at the technical level.I have delivered across the full fintech stack: KYC/IDV, ACH, card issuance, BaaS multi-tenant architecture, processor integrations, credit compliance, and sponsor bank models. That breadth matters when the platform has to serve regulated use cases reliably.Currently based in Los Angeles.

Experience

1. Lead Technical Product Manager - Data Engineering

   System1

   May 2023 — Present · Marina del Rey, CA, US

   I own the product roadmap for System1\'s data platform (the layer that ingests, normalizes, and serves structured data to business intelligence, data science, analytics, and external partners). The platform spans everything from raw API ingestion (Google, Facebook, TikTok, Bing) through semantic layer design, data quality, observability, and partner-facing reporting APIs.Over the past two years the scope has expanded significantly into AI-native tooling. I led the development of an agentic platform that delivers autonomous campaign management, text-to-SQL with semantic layer integration, automated pipeline alerts, and AI-generated analysis. This moved the platform from a passive data store into an active decision-support system.Some of the deliverables include:Developing LLM-powered enterprise data applications using Snowflake Cortex, semantic models, and Streamlit.Enhanced the analytic database for data quality and metric coverage.Delivered a channel locking solution that reduced anticipated ad placement clawbacks resulting in significant savingsDelivered a data pipeline observability dashboard that gave internal teams a single trusted view of pipeline health and reduced support inquiries.The stack includes Snowflake, DBT, ELT/ETL pipelines, Snowflake Cortex, Streamlit, and APIs across major advertising platforms. I work directly with data engineering, data science, business intelligence, and product leadership.

Education

• University of the Fraser Valley

  Information Technology

Skills

• Software Development
• Scrum
• Data Modeling
• Fintech
• Software Project Management
• Mdx
• Leadership
• Program Management
• Functional Requirements
• Agile Project Management
• Logical Data Modeling
• Integration
• Sql
• Online Advertising
• Big Data
• Sdlc
• R
• Digital Media
• Olap
• Data Integration
• Agile Methodologies
• Etl
• Enterprise Software
• Technical Product Management
• Dimensional Modeling
• Jira
• T-Sql
• Requirements Analysis
• Cloud Computing
• Microsoft Excel
• Systems Analysis
• Data Analysis
• Data Warehousing
• Project Management
• Web Services
• Software as a Service (Saas)
• Business Analysis
• Business Intelligence
• Confluence
• Database Design