A Senior Software Engineer at CiBo Technologies, Dick Wall work on large scale geospatial datasets in Scala. He has been developing in Scala since 2006, formed the Bay Area Scala Enthusiasts (one of the first Scala user groups) in 2007, and has been delivering Scala training since 2009 at all levels. He is a former host of the Java Posse podcast and a Scalawag (a Scala oriented podcast currently on hiatus). Recipient of the inaugural Phil Bagwell Award for Scala Community Service, Dick also revived and ran the SIP/SLIP Scala Process from 2015 to 2016.

In advance of his talk “Your Type System Working for You” at Scala Days in New York, we asked Dick about his Scala journey and the Scala community.

Rebecca Ely, or simply Ely, as she’s known in the Scala community, is an engineer on the Spark platform team at Bloomberg and an enthusiastic member of the SF Scala community. Her 2015 transition into tech was preceded by work as a federal acquisition consultant, math and science teacher, and volunteer monkey bather. She still bathes the occasional monkey.

In advance of her talk “Teaching Scala to the Statically Challenged” at Scala Days in New York, we spoke to Ely about her quitting a job in D.C., designing a folk dance choreography algorithm and her Scala journey.

As a software engineer at Spotify working on data and machine learning infrastructure,  Neville Li has been driving the adoption of Scala and new tools for data processing, including Beam, Scalding, Spark, Storm and Parquet. Prior to Spotify, he worked on search quality at Yahoo! and old school distributed systems like MPI.

We spoke with Neville in advance of Teaching Scala: A Roundtable Discussion at Scala Days in New York on June 20th, which he is joining as a panelist alongside the inventor of Scala language, Martin Odersky, Ryan Tanner (Twitter), Kelley Robinson (Twilio), Maciej Gorywoda (WIRE), Mark Lewis (Trinity University) and Heather Miller (Scala Center), and asked him about his Scala story.

A transgender, Canadian, open-source developer advocate at Google with a focus on Apache Spark, BEAM, and related “big data” tools, Holden is the co-author of Learning Spark, High Performance Spark, and another Spark book that’s a bit more out of date. She is a commiter on and PMC on Apache Spark and committer on SystemML & Mahout projects. In her own words, she was “tricked into the world of big data while trying to improve search and recommendation systems and has long since forgotten her original goal”.