Set team objectives and created KPI dashboards using AWS QuickSight to track progress based on millions of data points, which convinced key stakeholders to prioritize reliability.

Defined technical plan for reliability improvements and spearheaded development, which increased data pipeline reliability from 87% to >99% across the board, reducing time spent on support tickets and bugs.

Managed cross-functional projects with the data science team resulting in streamlined model development that saved $500,000 dollars a year and reduced the time to deploy models.

Architected 2 new API integrations with commodity ML providers and integrated 7 new proprietary models.

Introduced AWS Sagemaker into the media annotation pipeline reducing time-to-value for new proprietary models from weeks to days.

Diagnosed and fixed scaling issues with distributed systems, which helped hit the goal of doubling capacity every year.

Launched a serverless analytics pipeline for a new flagship product that handled 10 million rows of data per day.

Championed a testing culture by introducing end-to-end testing for data pipelines and directing work to increase unit test coverage from 23% to 63%.

Sped up a key ad analytics ingestion pipeline by 35% by maximizing I/O usage.

Working with my comanagers, doubled revenue by expanding offerings and lowering costs while fully paying off debts totaling over $20,000.

Developed new systems to speed up our hiring process, centralize our finances, and reduce time spent doing inventory.

Suggested and implemented improvements to the code base for the larger inventory