Never breaks the upstream job
Every data quality and cost pipeline I've shipped runs as a soft-fail observer: a failing check writes a finding row, it never raises and kills the parent job. A DQ failure is a data observation, not a pipeline outage.
$142K
platform spend brought under governance at Barton Malow
211
automated data quality checks shipped to production
10M+
records validated across telecom billing pipelines at Oracle
90×
faster billing automation built at Accenture
Top 10
of 60+ teams, Penn State Nittany AI Challenge 2026
The Pragmatic Builder
Everything is built on a production mindset.
"Understanding existing systems deeply before changing them, designing for the next person who has to maintain my work, and communicating technical findings in a way non-technical stakeholders can act on." That’s the standard I actually build to.
Idempotent by design
Every gold table load pairs with a post-write uniqueness check that runs on every execution, not just at build time, so reruns, backfills, and late-arriving data can't silently create duplicate rows.
CI-gated, AI-assisted
Every pipeline repo ships with lint + a schema validator tested against real broken input: a malformed rule or a broken job dependency fails the build before it fails in production. I use Claude Code across the full git lifecycle, including branching, commits, PR reviews, and merges, to move faster, but every change still ships through a branch, a pull request, and a green CI check before it touches main. AI accelerates the workflow; it doesn't bypass the gate.
Documented for the next person
Architecture docs, decision logs, and known-limitations sections ship with every pipeline, not just the happy path. The goal is that someone else can maintain it without asking me first.
01 · Experience
5+ years turning messy real-world data into decisions leadership can act on
Data Science Intern
Barton Malow Featured
- Built a Databricks Cost Analytics pipeline and 4-tab leadership dashboard from Unity Catalog billing/compute data, surfacing $142K in lifetime platform spend and $13.2K in idle resource cost across 885 unused objects. Automated an ownership-resolution hierarchy across 933 resources that cut the unowned-spend gap from 85.6% to 54%.
- Designed a Claude AI cost-attribution dashboard isolating agent query costs from shared Databricks serverless compute (20+ users, 8,000+ queries, $0.53 avg cost/query), revealing AI's share of warehouse spend grew 5.5× in 5 months (1.5% → 8.3%), giving leadership real-time cost visibility before it became a budget concern.
- Engineered a 211-rule automated data quality framework spanning 23 production tables in a $159B CRM pipeline, achieving 100% clean execution while using DQX's AI-driven profiler to accelerate future rule generation.
DatabricksPySparkSQLPythonClaude CodeGitHub Actions
Research Assistant, Data Science
Pennsylvania State University
- Developed forecasting models on historical attendance data, achieving 92% accuracy and enabling data-driven vendor allocation and capacity planning.
- Reduced event planning timeline 83% (12 months → 2 months) by building data-driven workflows, dashboards, and scenario simulations that aligned stakeholders on constraints and priorities.
- Prototyped autonomous AI agents for continuous auditing and ethical compliance, including WORM-based audit trails, ontology-driven fairness checks, and cybersecurity safeguards aligned with ISO/IEC 42001.
Statistical ModelingForecastingAgentic AIPythonSQL
Staff Data Consultant
Oracle Corporation
- Validated end-to-end billing data pipelines for 600K+ telecom subscribers using SQL-driven quality checks, anomaly detection rules, and reconciliation reports, maintaining 98%+ accuracy within SLAs.
- Built and automated KPI dashboards (churn, usage patterns) with 99% on-time delivery, enabling leadership to track performance in weekly reviews.
- Led onsite test efforts, coordinating with offshore analytics teams to deliver readiness dashboards supporting a successful, on-time go-live.
Oracle DatabaseSQLData AnalysisBusiness Analysis
Award Oracle "Best Upcoming Talent," FY23 Q3
Data Consultant
Accenture Solutions Pvt Ltd
- Identified and resolved 50+ recurring data quality issues in production billing datasets for a 4.5M-customer base, improving billing accuracy and customer trust.
- Automated batch bill-run workflows using SQL scripts and scheduling, cutting processing time from 1 day to 2 hours (90× faster) and manual effort by 92%.
- Designed a SQL-based data validation framework (row-level checks, reconciliation, exception flags) that reduced discrepancies by 60% and shortened month-end close by 10%.
SQLShell ScriptingExcelClient Communication
Award Accenture "Shared Success Catalyst," Addressing Client & Community Needs
02 · Featured Projects
Real systems, real numbers
Data Engineering
211checks
23tables
84%records flagged
Databricks Data Quality Framework
Automated data quality monitoring built on Databricks DQX. Surfaced that 84% of active records carried at least one issue, and root-caused a ~39% completeness gap in a core reporting table.
CI: lint + schema validation
Soft-fail: never breaks the upstream job
View repo →
$142Kspend governed
54%unowned spend (from 85.6%)
2×error caught pre-ship
Databricks Cost Analytics & FinOps
FinOps cost-attribution pipeline on Unity Catalog system tables. Cut unowned spend from 85.6% to 54% and caught a 2x measurement error in the AI-cost methodology before it shipped.
CI: lint + job-config validation
Idempotent: 0 duplicate rows on every rerun
View repo →
Scholar Swipe: Scholarship Scraper
Automated scraping pipeline extracting scholarship listings into a centralized PostgreSQL (Supabase) database, with upsert-based dedup and automated summarization.
View repo →Data Science / ML
AI Sentinel: Compliance Monitoring
Autonomous compliance agents detecting AI-driven regulatory risk in real time. Top 10 of 60+ teams, Penn State Nittany AI Challenge 2026. 5 detection rules mapped to CMS federal regulations (42 CFR §483).
View repo →Resume–JD Matching via Deep Learning
3-stage semantic ranking pipeline: TF-IDF baseline → SBERT embeddings → supervised neural refinement into a calibrated match probability. 120 resumes ranked against 2,277 job descriptions.
View repo →Worldwide LLM Sentiment Analysis
End-to-end NLP + geospatial pipeline tracking global sentiment toward LLMs across 305K+ tweets. Location-normalization cut unresolved geography from 72.8% to 43.85%.
View repo →Analytics Engineering / BI
Alzheimer's Market Overview (US)
TRx-based pharmaceutical market analysis across brands, specialties, and channels. 202,499-row dataset, built as parallel Python (Plotly) and Tableau dashboards for direct platform comparison.
View repo →Penn State Alumni Event Forecasting
Multi-year (2022–2025) event performance analysis with scenario-based 2026 forecasting, projecting 235 attendees and $49/attendee revenue via a blended trend + recency-weighted model.
View repo →03 · Research & Recognition
Published work and competitive recognition
Autonomous Multi-Agent Governance: AI Sentinel Framework for Mitigating Psychological Restraints in AI-Driven Fall Management
Accepted and presented at SEET 2026 (2nd International Conference on Software Engineering of Emerging Technologies), Penn State Behrend, PhD Research Track. Listed on page 76 of the conference abstract book. To be published in the official conference proceedings by Springer Nature.
View conference →AI Sentinel: Top 10 of 60+ Teams
Won the Prototype Phase and MVP Phase, advanced through funded phases to a Top 10 finish at the Pitch Contest, Hintz Family Alumni Center, University Park.
"Best Upcoming Talent" (FY23 Q3)
Recognized for exceptional contributions and high-impact performance on the Telia Company billing analytics engagement.
Student Senator
Representing students in discussions with university leadership; championing AI literacy and equitable AI access across Penn State's Commonwealth Caucus.
04 · Skills
Tools I actually ship with
Programming
Python (Pandas, NumPy, Matplotlib, Seaborn, scikit-learn, TensorFlow, PyTorch, Keras) · SQL · R · Java
Data Engineering & Cloud
Databricks · PySpark · Unity Catalog · Azure · AWS · Oracle Database · PostgreSQL · PL/SQL
ML & Statistics
Regression · Classification · Clustering · NLP · Time Series Forecasting · Feature Engineering · Model Evaluation (AUC, F1)
BI & Visualization
Tableau · Power BI · Plotly · Matplotlib · Seaborn
Dev Tools
Git · GitHub Actions · Jupyter · Jira
AI Tools
Claude Code · Claude Cowork · Claude Skills · Claude Projects · Claude MCP · ChatGPT · GitHub Copilot · Cursor IDE · Perplexity · Ollama · Google Gemini · Julius AI
05 · Education
Background
Pennsylvania State University
Aug 2025 – Dec 2026Master of Data Analytics · GPA 3.96/4
Statistical Analysis, Data-Driven Decision Making, Predictive Analytics, Deep Learning, Natural Language Processing.
KIIT University
May 2015 – May 2019B.Tech, Electronics & Instrumentation Engineering · GPA 3.3/4
Control Systems, Digital Electronics, OOP, Data Structures & Algorithms, Web Technology, Artificial Intelligence.
06 · Get in touch
Let's build something that ships.
Open to full-time Data Scientist / Data Engineer / Analytics Engineer roles starting Dec 2026.