Israel Herraiz
DevOps Engineer at google
Madrid, Community of Madrid, Spain
Summary
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RockstarIsrael Herraiz is a Strategic Cloud Engineer at Google with 17 years of experience helping large enterprises transform terabytes and petabytes of data into actionable insights using Google Cloud Platform. He combines deep technical hands-on work—contributing to high-profile open-source projects like Apache Beam and GoogleCloudPlatform/professional-services—with customer-facing performance tuning for data analytics and machine learning at scale. His background spans industry and academia, from leading data science teams at BBVA and Amadeus to teaching machine learning and directing a Master in Data Science, reflecting strong mentorship and curriculum-building skills. Notably, his Apache Beam contributions improved BigQuery integration and cross-cloud credential support, highlighting a practical focus on interoperable, production-ready data pipelines. With a PhD in Computer Science and earlier engineering degrees awarded with top honors, he brings rigorous academic foundations to pragmatic engineering and architectural decisions. Based in Madrid, he blends research-grade thinking with proven delivery in cloud-native data processing.
17 years of coding experience
Stackoverflow
1reputation
0reached
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Github Skills (15)
gcp10
javas10
kafka10
google-cloud-platform10
google-cloud-dataflow10
dataflow-programming10
bigquery10
aws10
dataflow10
apache-beam10
java10
scala10
streaming9
sql9
avro9
Programming languages (10)
Github contributions (5)
GoogleCloudPlatform/professional-services
Jan 2019 - Feb 2022
Common solutions and tools developed by Google Cloud's Professional Services team. This repository and its contents are not an officially supported Google product.
Role in this project:
Data Engineer
Data EngineerContributions:139 reviews, 19 commits, 74 PRs in 3 years 2 months
Contributions summary:Israel contributed significant Scala code focused on building a Dataflow pipeline. Their work involved creating a Dataflow pipeline to read data from Kafka, transform it, and persist the processed data into Avro files in Google Cloud Storage. This includes reading from Kafka using the KafkaIO library, transforming strings into objects, and then writing those objects into Avro files, demonstrating a strong understanding of data ingestion and processing techniques. The code modifications also showcase the use of Scio, a Scala library for Apache Beam, for building and running data pipelines on Google Cloud Platform.
google-cloudgoogle-cloud-platformgoogle-cloud-dataflowgoogle-cloud-mlgoogle-cloud-compute
apache/beam
Sep 2019 - Nov 2022
Apache Beam is a unified programming model for Batch and Streaming data processing.
Role in this project:Back-end Developer
Back-end DeveloperContributions:48 reviews, 18 commits, 27 PRs in 3 years 2 months
Contributions summary:Israel's contributions primarily focused on enhancing the BigQuery integration within the Apache Beam SDK. They added features such as the ability to specify a temporary dataset for query results and implemented options for setting the query location. Additionally, the user addressed issues related to authorized views and ensured correct timestamp handling within the Beam framework, specifically in the context of Katas, demonstrating a deep understanding of data processing and related Google Cloud services. The contributions also included adding support for BasicSessionCredentials for AWS credentials.
apache-beamstreaming-datapythonjavabig-data
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