Strategy & Alignment
- Aligns the technology roadmap with clinical, financial, and research goals.
- Owns governance, HIPAA compliance, and enterprise data reliability.
- Manages multi-cloud strategy across AWS and Azure for resilience and cost control.
Technology Leadership • Cloud • Data • AI
Building secure, intelligent systems that turn technology into business advantage.
Shaunjay J. Brown — Head of Technology & Information Systems
Technology leader with 7+ years building the data, cloud, and AI infrastructure that healthcare, finance, and research organizations depend on. I combine enterprise strategy with hands-on engineering fluency across AWS, Azure, Snowflake, Databricks, and agentic AI.
30%
Infrastructure cost reduction
40–70%
Performance improvements
7+Years in data, cloud & technology leadership
50+Automated data-quality rules delivered
60%Clinical data-latency reduction
HIPAAGovernance-first platform design
Scope of Leadership
A unified technology mandate across strategy, innovation, and operations.
Bringing the perspective of a CIO, CTO, and IT Director into one accountable leadership model.
Research & Innovation
- Evaluates agentic AI, LLM/RAG systems, and multi-agent orchestration.
- Moves product-facing data and AI initiatives from prototype to production.
- Builds compliance-aware AI with PII redaction, bias detection, and human review.
Operations & Team
- Runs infrastructure, data pipelines, and platform reliability.
- Owns CI/CD, observability, monitoring, and incident response.
- Coordinates delivery across engineering, analytics, and business teams.
Impact at Charterm Group
Data Engineer • Remote • January 2025–Present
Improved data freshness and reliability through real-time AWS Glue and Kinesis pipelines powering experimentation and KPI dashboards.
Reduced ETL runtimes by optimizing PySpark transformations across Databricks and Azure Databricks.
Lowered multi-cloud infrastructure costs while strengthening reliability across AWS and Azure.
Reduced manual reporting effort through automated lineage, validation, dbt, and Python workflows.
Improved query performance using partitioning, Z-ordering, and schema evolution across S3 and Delta Lake.
Raised data integrity by embedding governance and validation directly into the delivery lifecycle.
Applied Research & Innovation
Multi-Agent Mortgage Underwriting System
A compliance-aware agentic AI system designed to automate underwriting while preserving deterministic controls, explainability, and human oversight.
01
Multi-agent orchestration
Designed a LangGraph-based workflow spanning credit, income, asset, and collateral review.
02
Auditable RAG decisions
Built a ChromaDB retrieval pipeline for policy-grounded decisions and traceable evidence.
03
Risk and compliance controls
Added deterministic financial checks, PII redaction, bias detection, audit logging, and human-in-the-loop escalation.
Case Studies & Success Stories
From fragmented healthcare data to a reliable staffing intelligence platform.
This featured case study is written as an editable portfolio story. Replace the sample metrics and implementation details with your verified production results before publishing.
The challenge
A large healthcare network operating across multiple hospitals and care facilities faced a critical operational challenge: fragmented, manual reporting processes prevented leadership from obtaining a reliable enterprise-wide view of staffing performance. Each hospital operated independently using disparate systems, delivery mechanisms, and reporting standards, creating persistent data silos.
Source data arrived through multiple channels:
- Secure SFTP transfers delivering CSV, JSON, Excel, and other staffing exports.
- Internal REST API snapshots capturing facility-level operational records.
- Real-time Admission, Discharge, and Transfer (ADT) events from hospital information systems.
- Webhook-driven operational events from third-party clinical platforms.
Without a centralized data engineering platform, analytics teams manually collected files, validated schemas, corrected malformed records, reconciled inconsistent nursing-role classifications, and rebuilt metrics with spreadsheets and ad hoc scripts. Reporting latency ranged from several hours to multiple days because of upstream data-quality issues and irregular delivery schedules.
The solution
- Designed batch and real-time ingestion using S3, SQS, Lambda, Kinesis, and AWS Glue.
- Implemented Bronze, Silver, and Gold layers for traceability, standardization, and analytics.
- Added schema validation, duplicate detection, quarantine handling, lineage, and audit logging.
- Created staffing marts for shift fill rate, overtime, vacancies, agency usage, and labor cost.
- Established CloudWatch monitoring for stream latency, batch freshness, failures, and queue backlogs.
Illustrative outcomes
< 2 hrsTarget batch freshness
P95 < 60sTarget ADT stream latency
99%Pipeline success objective
< 0.1%Duplicate-record target
Portfolio note: These values are placeholders. Replace them with measured outcomes, customer-approved figures, or clearly labeled project targets.
Selected Projects
Technical work presented through business outcomes.
Each project card includes space for a GitHub repository and a walkthrough video. The two sample projects below are editable placeholders.
01
Healthcare Data Engineering
Healthcare Staffing Analytics Platform
Batch and real-time platform that unifies staffing, ADT, and facility data to improve coverage visibility, operational reporting, and data reliability.
02
Editable Placeholder
Multi-Agent Mortgage Underwriting System
Replace this description with the problem, architecture, controls, measurable outcome, and your specific contribution to the project.
03
Editable Placeholder
Cloud Data Platform Modernization
Use this card for a project involving migration, FinOps, governance, CI/CD, platform reliability, or performance optimization.
Prior Experience
Experience across healthcare, research, enterprise systems, and infrastructure.
Data Engineer
Charter Oak Health
- Reduced clinical data latency 60% by integrating patient and claims data from multiple EHR systems through AWS Glue and Kinesis.
- Implemented 50+ automated data-quality rules using dbt, Great Expectations, and Deequ, improving reliability 17%.
- Led a secure migration of patient and operational data to Snowflake and S3 while maintaining HIPAA compliance.
Data Migration Lead / Application Programmer Analyst
The New York Botanical Garden
- Spearheaded the Unit4 ERP migration across finance, operations, and HR while preserving data integrity and compliance.
- Reduced nightly job failures 15% and improved completion times 50% by re-engineering 12 SSIS integration packages.
Junior Linux Administrator
Boehringer Ingelheim
- Supported Linux-based enterprise environments and operational infrastructure.
- Contributed to system reliability, troubleshooting, and cross-team technical support.
Technical Foundation
Deep technical fluency for better executive decisions.
Cloud & Infrastructure
AWS Glue, Lambda, Kinesis, Redshift, DynamoDB, S3, IAM, Azure, Terraform, CI/CD
Data & AI Platforms
SQL Server, Snowflake, Databricks, dbt, Kafka, LangGraph, RAG, ChromaDB
Governance & Compliance
HIPAA, PII redaction, bias detection, Great Expectations, Deequ, lineage, audit logging
Languages & Scripting
Python, SQL, C++, Bash, automation, data modeling, performance optimization
Education & Certifications
Continuous learning across technology, analytics, and AI.
2026
Advanced Certificate, Applied Generative AI and Agentic AI
Johns Hopkins University
2022
Advanced Certificate, Data Science
Columbia University
2019
M.S. Business Intelligence
Villanova University
2010
M.S. Computer Science and Information Systems
Pace University
Beyond Technology
Curiosity, movement, and creative perspective.
Nature & Outdoors
Hiking, cycling, rock climbing, birdwatching, stargazing, and geocaching.
Intellectual & Analytical
Chess, puzzles, board games, escape rooms, language learning, and genealogy.
Media & Creation
Photography, podcasting, blogging, and turning complex ideas into accessible stories.
Let’s Connect
Technology leadership grounded in execution.
Open to conversations about technology leadership, data-platform modernization, cloud strategy, and responsible AI.