40M+
records unified
Golden records created across 10+ legacy systems at SLB.
Recruiting-first portfolio
Data Engineer + MSIS @ Kelley for enterprise systems, analytics, and AI
I build enterprise data systems that make reporting trustworthy, migrations safer, and analytics useful at scale. This portfolio connects SLB execution with current enterprise systems, cloud integration strategy, and AI work at Kelley.
Bloomington, Indiana
Open to data engineering, enterprise systems, analytics, and digital transformation roles.
Current focus
Enterprise data systems, digital enterprise architecture, and analytics-ready operating models.
Brand credibility
Signals from enterprise work, graduate training, and case competition wins.
Additional context
Selected outcomes
Measured execution, not generic claims.
99%
data readiness
Achieved through validation rules and quality checks for downstream analytics.
30%
faster sync
Delivered via SOAP-based material number reservation services.
3rd
place finish
Kelley MSIS CORE final project for TMHNA Digital Momentum.
Featured portfolio work
Case studies that connect technical execution to business value.
Enterprise data systems
SLB Enterprise Data Engineering
Scaled master-data and integration workflows across legacy systems to improve reporting trust, migration readiness, and analytics quality.
40M+ records unified
10+ legacy systems consolidated into governed enterprise data.
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Digital operating model
TMHNA Digital Momentum
Designed a target-state recommendation for TMHNA to align systems, processes, and finance data across TMH, Raymond, and THD.
3rd place finish
Future-state finance intelligence model across SAP S/4HANA, ECC, and Snowflake.
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Cloud transformation
Cloud Migration & Multi-Cloud Integration Strategy
Designed a 100% cloud migration roadmap and integration architecture for a mixed enterprise application estate spanning ERP, CRM, HCM, custom .NET, and IoT systems.
100% cloud migration plan
OCI, Azure, Salesforce, Workday, and iPaaS integration strategy in one roadmap.
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Applied AI research
Pothole Detection Using Deep Learning
Built an ADAS-oriented pothole detection workflow focused on data curation, benchmarking, and practical model selection.
82% model accuracy
ADAS-oriented vision workflow balancing inference speed and precision-recall trade-offs.
Read the case studyWhat I bring
Built for teams hiring at the intersection of data, systems, and execution.
Enterprise Data Foundations
Designing reliable pipelines, governance checks, and golden-record systems for reporting and analytics.
Digital Enterprise Systems
Connecting SAP, Snowflake, and cloud-aware process design into decision-ready operating models.
Analytics & AI Readiness
Turning architecture into scalable datasets, KPI definitions, and AI-enabled workflows.