VP of Data · Financial Services

BrianCronin

I build data organizations that actually work — and now I'm doing it with AI agents

Twenty-plus years in financial services data, from mortgage ops to running the enterprise data org at the nation's largest independent broker-dealer. Now I'm designing agentic AI systems that are transforming data environments 10x faster than traditional approaches. I don't just think AI-first at work — I manage my own investment portfolio with a 9-agent AI system that I can query by voice through Siri. Same leadership principles, radically different toolbox.

Agentic AI Work → View Career See What I've Built →

Brian Cronin

VP of Data · Charlotte, NC

Career at a glance

20+

Years in Data & FS

10×

AI Acceleration

SVP→

Fortune 500 FS Firm

AI-first

Data Leader

Domains

Agentic AI Agent Orchestration Enterprise Data Strategy Financial Services Insurtech Cultural Transformation

Featured Project · Live on GCP

Portfolio Intelligence

Two LangGraph pipelines power different sides of portfolio management. The Analysis Pipeline runs 9 agents in 3 tiers — scanning macro, tracking congressional trades, analyzing fundamentals, and synthesizing recommendations with Haiku-powered context routing between tiers. The Allocation Builder takes a target model and has 7 agents hunt for specific stocks and ETFs to construct a portfolio from scratch, with side-by-side scenario comparison. I can query either by voice through Siri or pull up the React dashboard on my phone.

LangGraph + CrewAI + Claude Google BigQuery React + FastAPI SnapTrade + Fidelity

Explore the Architecture →

System Architecture

AI Agents

LangGraph Pipelines

Voice+Web

Siri + React

About Brian

The short version

Brian Cronin

VP of Data
Financial Services & Insurtech · Charlotte, NC

I've been doing data work in financial services for over twenty years — mortgage, broker-dealer, fintech infrastructure, insurtech. Every stop taught me something different about what makes data organizations succeed (and what makes them fail).

Right now I'm leading an agentic AI programme that's getting 10x acceleration on data environment transformations. We're using AWS Kiro, Google Agentspace, Claude Code, and Snowflake Cortex to do in days what used to take months. It's the most exciting work I've done in my career, and it's not close.

I'm a firm believer that AI without governance is just chaos with better marketing. Every agent my team deploys has guardrails, human checkpoints, audit trails, and an off switch. In financial services, that's not optional — it's the whole point.

🤖

Agentic AI — Hands On

I don't just talk about AI strategy in meetings. I'm designing agents, writing skills, building orchestration frameworks, and shipping results. The 10x number isn't a slide deck — it's what my team is actually delivering.

🏦

Financial Services Through and Through

Insurance, wealth management, lending, fintech — I speak the language. Regulatory constraints, compliance data, risk environments. This is my home turf.

🔄

Culture Is the Hard Part

The technology is the easy part. Getting people to trust data, adopt new tools, and change how they work — that's where most transformations die. I've done it four times across four very different organizations.

What I Bring

I've built data orgs from scratch, inherited legacy messes, and figured out how to make both work. The common thread is always the same: get the right people, give them clarity, remove the blockers, and measure what matters.

The agentic AI work I'm doing now is the most impactful thing I've seen in twenty years of data. We're compressing months of migration work into days — not by cutting corners, but by letting well-designed agents handle the repetitive grind so my team can focus on the decisions that actually need a human brain.

The 10x number comes from real deliverables, not a pitch deck. Thoughtful agent design, proper guardrails, and a data foundation that was built right in the first place.

AI-First Leadership Principles

→Agents do the heavy lifting — humans make the calls

→Every agent gets an owner, a scope, and an off switch

→Governance isn't the brakes — it's what lets you go fast without crashing

→If you can't explain what an agent did and why, it shouldn't be running

Agentic AI Leadership

🟣 Active Initiative

What I'm building right now

My team is using agentic AI to do data transformation work in days that used to take months. We design agents with specific jobs, give them well-defined skills and clear boundaries, and orchestrate them across complex workflows. The result is up to 10x acceleration — and that number keeps climbing as the agents get smarter and the patterns get more repeatable.

🧠

Agent & Skills Design

Each agent gets a specific job — ingestion, transformation, quality, cataloguing — with composable skills it can reuse across different data domains. Clear boundaries, clear escalation paths. An agent that tries to do everything is an agent that does nothing well.

Agent design Skills architecture Autonomous execution AWS Kiro Claude Code

🔗

Multi-Agent Orchestration

Multiple agents working together on complex workflows — some in parallel, some in sequence — handling multi-step data transformations that used to need a full team and weeks of calendar time. The orchestration layer is where the real leverage lives.

Agent orchestration Multi-agent systems Google Agentspace Snowflake Cortex

⚡

10× Data Transformation

Schema migration, pipeline generation, data quality cleanup, documentation — stuff that used to eat up months of engineering time. Agents handle the repetitive work, humans review and approve. The timeline compression is real, and it compounds as patterns get reused.

10× acceleration Pipeline automation Schema migration Auto-documentation

🛡️

AI Governance & Guardrails

Every agent has a defined scope, data access controls, human approval checkpoints, audit trails, and explainability requirements. In financial services, you don't get to move fast and break things. You move fast and document everything. That's what makes this sustainable.

AI governance Guardrails Human-in-the-loop Audit trails Explainability

Agentic AI Stack

🔶

AWS Kiro

Agentic IDE & development framework

🔵

Google Agentspace

Enterprise agent orchestration platform

🟣

Claude Code

Agentic coding & automation

🔷

Snowflake Cortex

AI & ML within the data platform

10×

Acceleration in data environment transformation

Schema migrations, pipeline builds, data quality cleanups, cataloguing — the bread and butter of data modernization that used to eat months of engineering time. My team is finishing these in days now. Not by cutting corners. By letting agents handle the grind so our people can focus on the architecture decisions and business logic that actually need a human brain.

🔐

AI-First. Governance-Led.

Speed without governance is just a faster way to create problems. Every agent my team deploys runs within a governance framework — scoped access, human approval gates, immutable audit trails, explainability requirements, and clear escalation paths. I put as much thought into the guardrails as the agents themselves. That's the difference between doing AI well and just doing AI loudly.

Skills & Expertise

What's in the toolbox

Twenty years of building data organizations means you pick up a lot of skills along the way. Here's what I bring to the table — from hands-on agent design to boardroom strategy.

🤖

Agentic AI & LLMs

Agentic AI Agent design & skills Multi-agent orchestration AWS Kiro Google Agentspace Claude Code Snowflake Cortex LLM integration Generative AI AI governance Guardrails & HITL Responsible AI

🎯

Enterprise Data Strategy

Enterprise data strategy Data-centric culture Data as a product Data products Executive communication Board-level reporting P&L ownership Budget management Strategic roadmap Business alignment

🏛️

Data Governance & Quality

Data governance frameworks Master data management Data quality & observability Data catalog Metadata management Data lineage SOX / GDPR / HIPAA Regulatory reporting Risk & compliance data

⚙️

Data Engineering & Architecture

Data pipelines ETL / ELT Data lakehouse Snowflake dbt Databricks AWS / Azure Apache Kafka Cloud-native architecture Technology modernisation

📊

Analytics & BI

Self-serve analytics Business intelligence Semantic layer / metrics store Tableau / Power BI / Looker Predictive modeling ML infrastructure Customer experience analytics Data-driven growth

👥

Leadership & Org Building

Org design Team building & scaling Hiring & talent strategy Change management Stakeholder management Data literacy programmes Cultural transformation Cross-functional leadership OKR frameworks

Career Timeline

20 years of enterprise impact

PresentCurrent Role

VP of Data

Leading Insurtech Platform · Charlotte, NC

Leading enterprise data strategy and a ground-breaking agentic AI programme at one of the fastest-growing insurance comparison platforms in the US. Designing autonomous agents, composable skills, and multi-agent orchestration frameworks — delivering up to 10x acceleration in data environment transformation using AWS Kiro, Google Agentspace, Claude Code, and Snowflake Cortex. Simultaneously driving governance, data quality, and cultural transformation across the organisation.

10× data transformation acceleration

Agentic AI programme from zero

100+ insurance carriers in data estate

Prior RoleSenior Executive

Senior Vice President, Enterprise Data

Fortune 500 Independent Broker-Dealer · Charlotte, NC

Senior VP-level ownership of enterprise data at the nation's largest independent broker-dealer. Led multi-year data modernisation programme, self-serve analytics buildout, data governance framework, and cultural change initiative. Owned P&L, budget, and team strategy across a large, complex data organisation managing $900B+ in assets.

#1 independent broker-dealer US

$900B+ AUM on platform

6 acceleration cohorts, 100+ participants

Earlier CareerFinancial Services

Senior Data & Analytics Leader

Global Fintech Infrastructure Provider · Charlotte, NC

Data and analytics leadership at one of the world's largest fintech infrastructure providers, supporting banking, payments, and capital markets clients. Deep expertise in complex regulatory data environments and enterprise-scale systems.

Earlier CareerFinancial Services

Data & Analytics Leader

Mortgage & Credit Data · Financial Services

Built foundational expertise in mortgage and credit data within highly regulated lending operations — requirements analysis, data quality, and business analysis that have informed every subsequent leadership role.

1999 — 2003Education

BS, Mathematics & Computer Science

Buena Vista University · Storm Lake, IA

Measurable Impact

Results that speak

🤖

10×

Acceleration in data environment transformation through agentic AI

AWS Kiro · Google Agentspace · Claude Code · Snowflake Cortex

🏆

20+

Years of data leadership across financial services, insurance, and fintech

Mortgage · Broker-Dealer · Insurtech · Fintech Infrastructure

🏦

$900B+

Assets on platforms where enterprise data strategy has been led

Nation's largest independent broker-dealer

🔄

4×

Enterprise data transformations led across distinct FS organisations

Each at different scale and maturity stage

👥

100+

Data professionals developed through cultural acceleration programmes

Experienced-Based Acceleration — 6 cohorts

🛡️

AI governance frameworks deployed with zero major incidents across all agentic programmes

Guardrails · HITL · Audit trails · Explainability

Leadership Philosophy

How I lead

AI-first, governance-led

Agentic AI is the biggest accelerant data teams have ever had. But deploying it in financial services without guardrails isn't bold — it's reckless. I go hard on both the innovation and the governance because you can't have one without the other.

Culture eats technology for breakfast

The best data platform in the world is worthless if nobody trusts it or knows how to use it. I spend as much energy on literacy, buy-in, and change management as I do on the tech stack. Transformation is a people problem first.

Lead from behind

Give smart people clarity, remove the blockers, trust their expertise, and get out of the way. That beats command-and-control every time. The best work I've seen — including the agentic AI stuff — comes from teams that feel safe to experiment.

If it doesn't move a metric, it doesn't matter

Every data initiative should tie to something the business cares about — revenue, risk reduction, efficiency, customer experience. The 10x acceleration is great, but only if it's pointed at the right problems.

Speak their language, not yours

Compliance, risk, AUM, policy lifecycle — financial services has its own vocabulary. Twenty years of fluency in that language, plus the ability to explain agentic AI to a board in terms they actually care about, is what gets a data leader a real seat at the table.

Invest in your people obsessively

Every great data platform I've built was built by great people I found, developed, and kept. In the agentic AI era, human expertise matters more, not less — because agents are only as good as the people who design, govern, and improve them.

Side Projects & Thought Leadership

Beyond the day job

Agentic AI↗

Agentic Data Transformation

Building and deploying multi-agent systems for data environment transformation — designing agents with composable skills, orchestration frameworks, and governance guardrails that deliver 10x acceleration. Hands-on with AWS Kiro, Google Agentspace, Claude Code, and Snowflake Cortex.

AWS KiroGoogle AgentspaceClaude CodeSnowflake Cortex

Leadership↗

Leading From Behind

Published perspective on servant leadership — creating conditions for a team to excel consistently outperforms top-down command. Widely shared across the data and FS leadership community.

Thought LeadershipPublished Article

AI in FS↗

GenAI for Customer Experience

Guidance on integrating generative AI into customer-facing financial services products — covering enterprise adoption challenges, change management strategy, and value realisation for both employees and customers.

GenAI / LLMCX StrategyFinancial Services

Data Culture↗

Experienced-Based Acceleration

Designed and ran a multi-cohort data acceleration programme reaching 100+ professionals across 6 events — elevating data foundations, literacy, and culture across a large enterprise.

100+ Participants6 CohortsEnterprise Scale

Data Revenue↗

Data Monetization Pioneer

Pioneered a Fortune 500 financial services firm's first successful data-driven revenue stream — designing and delivering a machine learning platform that transformed internal data assets into a new line of business. Proved that enterprise data organisations can be revenue generators, not just cost centres.

Machine LearningRevenue GenerationFinancial ServicesFirst-of-its-Kind

Community↗

Data & AI Leadership Network

Active mentor and connector across the data and AI community in Charlotte and beyond — with a track record of investing in the careers of data professionals navigating the agentic AI era.

Charlotte, NC500+ ConnectionsMentorship