I build warehouse models, KPI systems, and reporting workflows that teams can rely on.
Across these roles, I have usually taken fragmented operational data and turned it into outputs a team can trust, explain, and use.
GTM Data Engineer
I build GTM data systems that turn fragmented source data into reliable revenue, lifecycle, and reporting workflows.
Customer identity stitching and attribution · ELT reliability and warehouse modeling · Cross-functional metric ownership
- Unified CRM, GA4, product, billing, and support data into a governed Customer 360 model, raising attributable revenue coverage from 48% to 86%.
- Designed attribution logic and lifecycle reporting that reduced reporting lag from 6 days to 1 day for GTM stakeholders.
- Introduced dbt tests, Airflow monitoring, lineage, and CI patterns that pushed pipeline reliability to 99.6% and reduced downstream bad-data incidents.
Data Analyst Intern
I replaced manual reporting with warehouse-backed dashboards that made logistics KPIs easier to trust and act on.
KPI governance and semantic consistency · Self-serve BI and operational reporting · Performance tuning for analytics workflows
- Consolidated 20+ conflicting business metrics into a governed KPI layer for product, operations, and finance stakeholders.
- Built dashboards and QA workflows that reduced manual reporting time while improving executive adoption and trust.
- Improved refresh performance and reporting reliability through star-schema modeling, Azure SQL, and targeted DAX optimization.
Brokerage Data Administrator
I worked close to messy operational documents, OCR-assisted extraction, and compliance workflows, building the judgment layer between raw inputs and reliable downstream records.
Semi-structured document ingestion · Exception handling and QA workflows · Compliance visibility and SLA support
- Supported OCR and NLP-assisted extraction workflows for customs brokerage inputs with validation, routing, and human review for low-confidence outputs.
- Improved operational transparency by standardizing records used for compliance tracking, backlog visibility, and downstream reporting.
- Helped turn fragile intake processes into more reliable datasets and review workflows for high-risk operational work.
Business Analyst Intern, Product Analytics
I built product analytics and retention workflows that connected event data, experimentation, and predictive scoring to better product decisions.
Funnel and cohort analysis · Experiment measurement systems · Churn and retention modeling
- Built reusable funnel and experimentation readouts that helped identify onboarding friction and improve activation and completion metrics.
- Delivered predictive retention workflows that prioritized high-risk cohorts and linked model outputs to intervention decisions.
- Improved analytics reliability with structured Snowflake refresh patterns and decision-ready reporting for product stakeholders.
Venture Capital Intern
I used structured analytics, prospect scoring, and lightweight experimentation to improve sourcing quality and decision readiness.
Rules-based scoring and prioritization · Commercial experimentation · Executive reporting and synthesis
- Doubled weekly qualified leads by automating prospect list building and testing outreach variants with simple but disciplined measurement loops.
- Framed ambiguous commercial questions into structured reporting, research, and prioritization workflows for leadership.
- Used lightweight analytics to improve both decision speed and the quality of follow-up actions.