Nathaniel A.

• Contributed to large-scale implementation of a new financial accounting system, Oracle FAH. Tasked with system cutover and reconciliation vs. Airbnb’s legacy finance system covering $40B+ of transaction volume. − Leveraged end-to-end understanding of the legacy finance systems data flow to design a testing plan from inception to completion. Designed data testing frameworks and SQL queries to allow for reconciliation and anomaly detection between the 2 financial systems and worked with cross-functional teams to investigate and resolve some of the most complex platform data issues to ensure the financial data was timely and accurate. − Within 6 months of FAH implementation and testing the team was able to fully cutover to a new accounting system without significant financial material differences with the legacy system. • Transformed the close and reporting processes by championing automation. Built automated reporting for finance month-end and quarterly-end processes such as key accruals, revenue reporting, control analytics, and procedures. Owned multiple key analytics and dashboards built using Tableau and Apache Superset. − Enabled the company to speed up closing the books cycle from up to 2 weeks to less than 5 days, improve accuracy of financial data delivery, and reduce auditing timeline by 66%. • Served as main point of contact for Platform Accounting Analytics, to deliver key financial metrics to the head of finance platform controllership, to use in memos and decks for executives, the board of directors, and investors. • Contributed to a corporate SOX control initiative to ensure the completeness and accuracy of Airbnb’s financial data. − Developed the SQL code and Python workflow to create an automated order to cash process to calculate and explain Platform Revenue Take Rate. The automated pipeline reduced the OTC process by 3 days, monthly, and increased visibility to platform pricing and revenue recognized allowing for a smoother internal audit.

Contract via Vaco SF @ Google Collaborated with team members to expand dashboarding and reporting of the Purchases on Google program. • Developed SQL scripts, data pipelines, workflows, reporting tables, and data visualizations for the Purchases on Google program, paving the way for automated self-serve reporting that allowed business partners to see real-time KPIs including click metrics, sales/product metrics, and product feed data quality metrics. • Created an automated SQL workflow for Purchases on Google (a new product for Google Shopping) that performed data checks on new merchant accounts to identify potential issues with product offer feeds and onboarding. − The SQL pipeline would send out emails to new merchant onboarding account managers to reach out and resolve the issues, expediting the onboarding process, and identifying data issues to be quickly resolved. • Optimized Python application for alerting business analysts and program managers to increase efficiency. • Supported and created documentation for Google Developer API for Google Shopping. • Developed ad-hoc SQL queries for analysis and studies to answer key business questions.

Joined SolarCity as a Finance Operations Analyst and focused on identifying and improving efficiency of multiple workflow processes via SQL and increased automation. After developing multiple SQL and Python solutions for Finance Operations, joined the Engineering team as a QA Engineer, to test SOX compliant software and develop non-SOX software for a new battery system product. • Took the initiative to learn SQL and Python through online courses, developing SQL reports, and Python tools to automate the Solar Performance Guarantee calculations, refunds, and invoicing. − Increased productivity by enabling agents to quickly access the data and automate the performance calculations, honoring the Solar Performance Guarantee of 130% when compared to manual workflows. • Created a Python tool that allowed business partners to connect to an API and quickly see data visualization and analytics on battery system performance and financial savings. − New tool was used to provide real data and visualization in the field with large-scale clients to win new battery system contracts and provide metrics for existing customers. • Created: 1) SQL reports to show trends in performance and expense analysis of company’s portfolio; 2) SQL reports that analyzed the performance of 280,000 solar systems; 3) Python application that performed diagnostic checks on the SQL database and alerted the appropriate team of any abnormalities via Slack. • Debugged and maintained: 1) SQL stored procedures and function that auto-registered new solar system components; 2) Python API’s (Flask) with SQL read and write privileges for battery system performance.