Microsoft Fabric
Benjamin DeMartino
Data Engineer and Analyst
Ballwin,MO
Summary
Results-driven Data Engineer and Analyst with a proven track record at FanDuel Sports Network, specializing in data pipeline design and optimization. Experienced in data modeling and visualization, I enhance decision-making through providing actionable insights. Adept at collaborating with stakeholders, I deliver high-quality analyses that drive strategic initiatives and improve overall performance.
Overview
7
7
years of professional experience
Work History
Data Engineer
FanDuel Sports Network
St. Louis, MT
04.2025 - Current
- Built self-serving data models and APIs for FDSN teams to understand subscription and consumption patterns within their fanbase.
- Deployed numerous production facing data pushes, following Medallion Architecture standards
- Collaborated with stakeholders to gather reporting requirements and insights.
- I wrote Fabric notebook code (SparkSQL/PySpark) for intermediate table building.
- Built semantic models in Fabric, following Star Schema and Snowflake architecture.
- Developed interactive dashboards using Power BI for data visualization.
- Developed and maintained data models to support analytical needs across teams.
- Optimized database performance through regular monitoring and tuning activities.
- Worked with internal teams to understand business needs and changing strategies.
- Implemented ETL processes to streamline data integration from various sources.
Data Solutions Analyst
Zion and Zion
12.2022 - 05.2025
- Developed comprehensive data warehousing solutions with use of various software and platforms.
- Built large scale data tables through query writing and creation of data models.
- Created data visualizations for interactive client engagement and actionable insight yielding.
- Assisted in the development of company-wide best practices for solution analysis, increasing overall effectiveness and consistency across team.
- Delivered timely, high-quality analyses to support senior management in strategic decision-making processes.
- Build cohesive data strategy documentation for use-case driven reporting and implemented strategies via tagging and analytics tool platforms.
Campaign Assistant
Coegi
01.2022 - 08.2022
- Drove data-influenced decisions for campaigns and businesses.
- Reviewed and used data to make recommendations to improve campaign performance, media touchpoints and journey.
- Actively participated in brainstorming sessions contributing innovative ideas that positively impacted overall strategies.
Marketing Analyst
University of Missouri
01.2019 - 01.2022
- Started as digital marketing analyst intern, promoted to student employee.
- Assessed KPIs to achieve in-depth understanding of campaign performance.
- Built campaigns for search ads, display ads, and shopping ads, targeting select audience segments.
- Created main search ads campaign that brought in over 500k in attributed revenue
Education
BBA - Digital Marketing
University of Missouri
Columbia, MO12.2021
Skills
Data pipeline design
Data modeling
Data warehousing
Machine learning
Database optimization
API development
Data Insights
Data visualization
API data ingestion
Data integration
Data analysis
Data quality assurance
SQL expertise
Microsoft Azure
Query writing
Code refactoring
Portfolio
Snowflake Schema
Star Schema
Software
Power BI
DBT
Snowflake
Github
Google Cloud Console
Tableau
The Trade Desk
DV360
Google Tag Manager
Google Analytics
Looker Studio
Accomplishments
- Led a full rebuild of the subscription lifecycle model, replacing daily full-table rebuilds and premature aggregation with an event-driven, user-journey-based “Uber” model that tracks each subscriber’s complete lifecycle across trials, promos, engagement, pauses, cancellations, and churn.
- Re-architected consumption analytics from the ground up, replacing a poorly modeled, multi-fact design with a clean star schema; created an upstream layer to reduce Google Analytics processing from 16TB/day to ~4GB/day using incremental logic instead of full rebuilds.
- Integrated AI-assisted text classification into data pipelines to normalize and enrich messy sports metadata (e.g., team names, home/away indicators), improving data usability and downstream reporting accuracy.
- Unified DTC and Amazon consumption data into a single conformed fact table, enforcing ID-based joins, separating facts from dimensions, and leveraging Power BI semantic modeling best practices to significantly improve performance, correctness, and maintainability.
- Enabled true customer journey and churn attribution analysis, allowing stakeholders to trace individual user behavior end-to-end and understand why users convert, engage, pause, or churn — not just top-line counts.
- Built 'Winback' data model and Power BI Report for stakeholders to analyze effectiveness of campaigns shipped to churned users.
Timeline
Data Engineer
FanDuel Sports Network
04.2025 - Current
Data Solutions Analyst
Zion and Zion
12.2022 - 05.2025
Campaign Assistant
Coegi
01.2022 - 08.2022
Marketing Analyst
University of Missouri
01.2019 - 01.2022
BBA - Digital Marketing
University of Missouri