Before you hire a firm, see what it has built.

Oct 2022 – Jun 2025

A governed Iceberg lakehouse for a major research university, with auto-relationalization of Workday and PeopleSoft data and a 4,000-table student warehouse.

• Enterprise data platform and warehouse: natural-language query, an auto-relationalization engine, and a governed Iceberg lakehouse.
• Auto-relationalization converts Workday and PeopleSoft data into governed tables with no manual schema mapping, with referential-integrity and schema-evolution standards across a Bronze→Silver→Gold warehouse of 300+ tables (1M+ records/day).
• Airflow replaced with event-driven serverless orchestration — dynamic orchestration and far lower operational overhead.
• Consolidated EMR/Iceberg student data warehouse processing 4,000 tables every 6 hours.

Jan 2022 – Oct 2022

Company-wide dbt and Snowflake standards on a Marketing data platform later adopted by Revenue, Sales, and Product.

• Enterprise data-modeling standards on dbt and Snowflake, adopted company-wide.
• Onboarding so new teams could serve themselves onto DAAP — data as a platform — without waiting on a central team, cutting integration from weeks to days.
• Cost-optimization and governance policy that reduced platform cost 40% while improving performance, with data quality and lineage on the Glue Data Catalog.
• Offshore engineering team mentored on AWS, serverless architecture, and infrastructure-as-code.
• Platform expanded from Marketing into Revenue, Sales, and Product — Salesforce's primary cross-functional data platform.

Jan 2021 – Jan 2022

On-prem Hadoop to an AWS lakehouse for a Fortune 500 financial-services client, with real-time pipelines at a million events a day.

• Hadoop to AWS lakehouse migration, cutting infrastructure cost 70% and improving query performance 5x.
• Event-driven pipelines on Kinesis, Lambda, and DynamoDB for real-time processing at 1M+ events/day with column- and row-level security.

Mar 2019 – Feb 2020

Snowflake migration and Kubernetes-native orchestration for Wiley Publishing, Integral Ad Science, and Smart & Final.

• Snowflake migration and Kubernetes-native orchestration across Wiley, Integral Ad Science, and Smart & Final.
• ML and data-engineering workflows at Wiley supporting downstream machine-learning models.

Apr 2017 – Mar 2019

AWS analytics environment — data lake, Redshift, Athena, and QuickSight — for self-serve, real-time restaurant POS analytics.

• Data lake and analytics layer on Redshift, Athena, and QuickSight.
• Operations teams given self-serve access to real-time restaurant POS analytics.