I started an analytics team in an org responsible for Sponsored Ads campaign management and reporting in Amazon Ads. I lead two other business intelligence engineers in performing deep dives into product launches, experiments, and supporting business review reporting for org leadership.I have enabled our org to measure more than $300M in incremental revenue by creating the datasets used in our experiment analyses and utilizing my business understanding to develop revenue models where automated A/B experiment tools could not due to low adoption of features and noisy data. I serve as the subject matter expert for advertiser-facing experiments across all of Amazon Sponsored Ads.I built a data mart to enable teams to calculate daily advertiser search impression, click, and order share metrics at scale for the first time ever in Amazon Sponsored ads by processing more than 100B records a day. This data mart has been used by my team and others to develop recommendations for advertiser budgets and keyword bids to help them achieve their advertising goals. I designed this data mart to cover all applicable dimensions and metrics so that we would be able to calculate these metrics at any granularity necessary for an analysis. I also created aggregated weekly and monthly versions where necessary to improve query performance and significantly reduce query costs.I migrated our team's ETL jobs to an infrastructure as code package now managing hundreds of ETL jobs a day as the only data engineer on the team. I helped influence other team's within the Advertiser Experience org to adopt the same development patterns.I created Tableau and QuickSight dashboards to enable product leaders to monitor and deep dive their features.

I designed and built AWS Marketplace's data lake for internal analytics using Amazon Redshift, EMR, AWS Glue, Python, and an internal job scheduler. This new data lake migrated internal analytics usage off of the production Redshift cluster and gave the internal teams the ability to use Spark and Python to automate ETL jobs. This code package and infrastructure is still being used by the team more than 3 years later.

I successfully migrated the data ingestion for 50+ data sources to a centralized AWS Data Lake for a Redshift cluster serving AWS customer-facing reports. Identified multiple data quality issues in the AWS Data Lake while doing data quality checks and escalated them to the owning team to get them fixed. I completed this project with zero customer facing issues, and also applied Redshift table design best practices during the migration process to add the appropriate query optimization techniques including sort keys, distribution keys, and column encoding.Created scalable, self-serve reporting solutions for internal data consumers using Tableau and AWS QuickSight. These dashboards were used by the AWS Marketplace technical account manager team to run their weekly business reviews, report on their metrics to leadership, and manage pre-Re:Invent activities. These reports completely automated the prior Excel-based reporting the team was using.

Designed, built, and maintained a multi-terabyte data warehouse and ETL pipeline using Amazon Redshift, S3, AWS Glue, and EMR for an Amazon Advertising team.Create scalable, self-serve reporting solutions for internal data consumers using Tableau and AWS QuickSight.

Develop BI applications using SAP HANA and Tableau.

Lead SQL Developer on a team that worked closely with the California Department of Finance to publish the Governor's Budget for the State of California. Built reports in Oracle BI Publisher based on data extracted from Hyperion Planning and assisted with ETL tuning.

Create class content including homework assignments and tutorials for database classes using SQL Server, SQL Server Analysis Services, and SQL Server Reporting Services, and Tableau. Tutor students on database design, SQL, and using SAP ERP.Developer for the Asphalt Research Consortium website using ASP.NET and SQL Server.

Write scripts to automate business processes, maintain and develop Access databases, participate in continuous improvement projects.

Update and maintain content on the College of Business website, find and troubleshoot bugs in existing code, and design and implement new features.