Camila Perez

About Camila Perez

I’m a data analyst at Ticketmaster supporting Fraud Prevention operations as the sole data function for my team. I work across analytics, business intelligence, and data quality; analyzing large-scale transaction datasets and building the data foundations that help my team make faster, more accurate decisions.My background in finance and audit at PwC, EY, and Merck gives me a unique perspective on data work. I understand not just the technical “how” but the business “why”; which helps when deciding what data problems to solve and in what order.WHAT I DO: • Work with datasets at scale (5M-17M+ rows monthly, multi-year analysis) using Databricks SQL. • Build dashboards and reports in Tableau, Domo, and Databricks for operations and leadership. • Design data quality improvements and schema optimization for fraud prevention systems. • Create transformation workflows using Tableau Prep and Domo Magic ETL. • Support self-service analytics by building views, tables, and providing SQL guidance to team members. TECHNICAL ENVIRONMENT:SQL (Advanced)| Databricks | Delta Lake | Tableau | Domo | Python | Splunk | Data Quality | Schema DesignI’m continuously learning data engineering practices to better support my team. Always interested in connecting with data professionals working on analytics, BI in entertainment/tech, or anyone building data capabilities in small teams.

Experience

1. Business Analyst (Data Analytics)

   Ticketmaster

   Sep 2022 — Present · Seattle, WA, US

   Sole data analyst supporting Fraud Prevention operations, analyzing large-scale transaction data and managing data infrastructure. Deliver monthly metrics reporting, ad-hoc analytics, data quality improvements, and self-service BI capabilities.DATA INFRASTRUCTURE & QUALITY: • Design and implement schema optimization for fraud prevention databases, improving organization, removing redundancies, and creating analytics-ready structures for BI and operational use. • Validate data integrity during platform migrations, ensuring accuracy and business continuity. • Develop data documentation and standardization frameworks to improve discoverability and reduce query complexity. • Research available data assets, build relationships with data-owning teams, and negotiate access to expand analytical capabilities.BUSINESS INTELLIGENCE & REPORTING: • Deliver monthly executive reporting and ad-hoc analytical requests across fraud prevention, payments, and chargeback domains. • Query and analyze datasets with 5M-17M+ rows monthly and multi-year historical data using Databricks SQL. • Build operational dashboards in Tableau, Domo, and Databricks supporting operations and strategic leadership. • Create data transformation workflows using Tableau Prep and Domo ETL Builder to automate reporting preparation. • Develop automation solutions to streamline recurring reporting processes.SELF-SERVICE ANALYTICS: • Create reusable views and tables in Databricks using SQL to enable team self-service analytics and reduce ad-hoc dependency. • Provide SQL query development and analytical guidance for fraud rule optimization, investigations, and reporting. • Coordinate with data engineering teams to expand data sources and improve accessibility.TECHNICAL ENVIRONMENT: Databricks | SQL | Delta Lake | Tableau | Domo | Python | Splunk

Education

• Pontificia Universidad Católica de Valparaíso

  Auditor Accountant, Accounting and Finance

  2014

• Hult International Business School

  Master's in Business Analytics

• Pontificia Universidad Católica de Valparaíso

  Bachelor of Science in Business and Economics, Accounting and Finance

  2014