In the past decade or more, two technology trends have intersected: the cloud, with its abundance of on-demand, computing resources, and the ubiquity of data. This makes it cheap to learn from data and makes previously intractable problems feasible. In my work, I have leveraged this to build more efficient, smarter, and easier to use cloud data systems.I'm currently focusing on the most important things in life - family and pursuing my passions in cloud and data.At Google, I was VP of Engineering for Streams and Lakes - the data integration, streaming, and open source analytics services on Google Cloud. At AWS, I ran Search Services which includes Amazon OpenSearch/Elasticsearch Service, the OpenSearch project, Open Distro, and Amazon CloudSearch. I also launched and ran two fast-growing cloud services, AWS Lake Formation and AWS Glue, and managed engineering teams in Amazon Redshift.Prior to Amazon, I was co-founder and CEO of Amiato (2011-2014), a managed ETL service in the cloud (acquired by Amazon). From 2004-2011, I was a principal scientist at HP Labs where my work spanned large-scale data management, distributed systems, and energy-efficient computing. This work has been published in top-tier database and systems conferences and has won several awards. Prior to HP, I received my PhD from U.C. Berkeley (2004) for adding parallelism, fault-tolerance, and load-balancing to the TelegraphCQ data-stream processing system. In 1999, I worked on the IBM DB2/UDB database. I received an MEng in 1997 and BS in Computer Science and Physics in 1996, all from MIT. In my spare time, I serve on the Sort Benchmark committee.