Ed Pearson
Principal, Analytics8
Nashville, Tennessee, United States
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Ed, currently a principal at Analytics8 helping lead the Databricks practice, is a data leader with more than two decades of experience architecting and delivering modern data platforms that transform how organizations use data to drive innovation and business outcomes. His work spans Fortune 500 companies to high-growth startups, with deep expertise across Databricks, Azure, Snowflake, AWS, and NoSQL technologies. Beyond solution delivery, Ed is passionate about growing the data community, having founded the Nashville Data Engineering Meetup and the DataTune conference to foster collaboration, learning, and career development. Speaking regularly across the United States on data engineering, lakehouse architecture, and modern ELT practices, Ed shares real-world insights and helping teams and leaders unlock the full potential of their data.
Area of Expertise
Topics
Implementing Data Governance Using Unity Catalog on Databricks
With the explosion in data that we are all experiencing, the need to manage and govern our business’ critical data assets has grown more critical, but also made it harder. Databricks’ Unity Catalog offers a unified data governance offering to accelerate and simplify metadata management for your entire data estate.
We will explore the challenges of data governance that Unity Catalog addresses. We will discuss how it can help alleviate data silos throughout your enterprise. How it simplifies a single pane of glass view of data lineage as it winds it through your data lakes and warehouses. How to use Delta Sharing to help create data products and more easily share your analytics with external users and customers, while still maintaining tight controls. What Lakehouse Federation can enable by bringing other data systems into Unity Catalog, including Synapse, Snowflake, and Redshift. Lastly, with the comprehensive auditing you can see who is using what data and how, ensuring compliance with internal and external control requirements and giving you insight into how your enterprise uses its data and where there are opportunities to expand.
Simplify your ELT: Using Lakeflow and Declarative Pipelines in Databricks
As data engineers, our real value isn’t writing one-off pipelines - it’s delivering reliable data that drives business outcomes. In this session, we’ll explore how Databricks’ new Lakeflow Connect and Declarative Pipelines features make it easier than ever to build reusable, maintainable ELT workflows in SQL.
We’ll start by showing how Lakeflow Connect accelerates ingestion from popular sources like Salesforce and Microsoft SQL Server (on-prem or in the cloud). You’ll see how to handle schema changes, enable CDC, and selectively load objects with minimal code.
Next, we’ll move into transformation with Declarative Pipelines (formerly Delta Live Tables), demonstrating how to define medallion-layer pipelines using parameterized SQL that’s portable across environments. We’ll walk through how expectations, merges, and autoloader complexity are abstracted away, enabling your team to deliver faster.
By the end of the session, you’ll see an end-to-end demo that takes data from source systems through bronze, silver, and gold layers — ready for analytics — and you’ll leave with practical patterns you can use to accelerate your own ELT development in Databricks.
Finding Your Spark: Unleashing Analytics with Python in Fabric and Databricks
Spark is the platform for compute on big data workloads in the cloud and underpins the two analytics platforms in Azure, Databricks and Microsoft Fabric. Python is the primary language for building modern data pipelines and to best leverage the capabilities of spark.
In this session we’ll walk through how best to develop in Python and notebooks across both Databricks and Microsoft Fabric, with a specific emphasis on developer workflow, performance tuning, and “how to actually build like a pro” in each environment.
We’ll cover:
• Development environment and project layout
• Modularity and reusability
• Compute optimization
• Performance tuning for Spark DataFrames
• How each platform uses GenAI assistants to speed development
This isn’t a high-level comparison, with demos in both platforms, we will get you up to speed and ready to output efficient, clean code ready for production environments.
BrickCon - A Databricks Community Conference Sessionize Event
SQL Saturday Jacksonville 2025 Sessionize Event
SQL Saturday Baton Rouge 2024 Sessionize Event
Data Saturday Atlanta Sessionize Event
SQL Saturday Baton Rouge 2022 Sessionize Event
SQL Saturday New Jersey 2022 Sessionize Event
Data Saturday Southwest US Sessionize Event
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