Daniel Tomes
Principal Architect at Databricks
Raleigh, North Carolina, United States
Summary
👤
Senior🎓
Top SchoolDaniel Tomes is a Principal Architect at Databricks with 11 years of experience designing and delivering data platforms and developer accelerators across enterprise and cloud environments. He blends deep hands-on expertise in Spark, Scala, Python, Java, R and SQL with strong systems skills in Linux, Bash and containerization to solve complex analytics challenges. Daniel has progressed through solutions and practice leadership roles at Databricks and Cloudera after a foundation in enterprise architecture at ConocoPhillips, giving him a rare mix of field-facing consulting and product-focused architecture. Based in Raleigh, he enjoys digging into problems personally and building reusable accelerators that help teams move faster. His background in MIS and an MBA complements his technical work with a practical focus on adoption, compliance and change management.
11 years of coding experience
8 years of employment as a software developer
Portuguese Portuguese, Portuguese Portuguese at Unifesp - Universidade Federal de São PauloMaster of Business Administration (MBA) Management Information Systems General, Master of Business Administration (MBA) Management Information Systems General at Oklahoma State UniversityBBA Management Information Systems & International Business, BBA Management Information Systems & International Business at University of Oklahoma
Spanish, Portuguese
Github Skills (69)
apache-spark10
python10
pyspark10
feature-engineering10
smote10
delta-live-tables10
monitoring10
faker10
ml10
synthetic-data10
spark10
databricks10
spark-streaming10
scala10
information-gain10
Programming languages (7)
Github contributions (5)
databrickslabs/feature-factory
Oct 2019 - Oct 2022
Accelerator to rapidly deploy customized features for your business
Contributions:2 releases, 9 reviews, 6 commits in 3 years
deploymentcustomizedacceleratordocker
databrickslabs/overwatch
Mar 2020 - Jan 2023
THIS PROJECT IS DEPRECATED. Capture deep metrics on one or all assets within a Databricks workspace
Contributions:26 releases, 368 reviews, 555 commits in 2 years 10 months
databricksmonitoring
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