# Controlled Data Movement

USAA and Wells Fargo · 2020 – 2024 · Role: Architect at USAA; Principal Architect at Wells Fargo

> A configuration-driven, secure data movement pattern built at USAA to move 25B+ records a day, then carried to Wells Fargo as a bank-wide framework for analytics and AI.

- **25B+** records per day at USAA
- **20x** scalability in the next-generation platform
- **99.9%** service-level objective

## Problem

Analytics and machine learning need large volumes of sensitive data in the cloud, moved reliably, with every control a regulator would expect.

## Approach

- At USAA, architected a configuration-driven pipeline moving 25B+ records and 800,000 files a day into AWS and Snowflake.
- Delivered a next generation with 20x scalability, 10x lower latency and a 0.01% exception rate at a 99.9% SLO.
- At Wells Fargo, worked with data leadership to turn the blueprint into a bank-wide controlled data movement framework and archetype.

## Governance

- Strict data isolation, granular access control and perimeter-based ingress and egress rules.
- Column-level encryption and de-identification for sensitive data.
- Automated audit logging, validation, rule-based reprocessing, lineage and catalog integration.

## Outcome

- A resilient data backbone for analytics and AI at two regulated institutions.
- Observability, lineage and catalog integration built into the pattern from the start.

## Lesson

Make the secure path configuration, not custom code, and teams will choose it.

Technologies: AWS S3, Snowflake, Perimeter security, Data loss prevention, Lineage and catalog, Observability

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Muthukrishnan (Muthu) Bommiah · https://muthub.org · Views are my own and do not represent my employer.