Dan Sedov
Senior Software Engineer at Datadog
Greater Paris Metropolitan Region France
Summary
👤
Senior🎓
Top SchoolDan Sedov is a Senior Software Engineer and Java-certified technologist with two decades of experience focused on middle and data tiers, now leading engineering efforts at Datadog after multiple senior and team lead roles at Google. He blends hands-on backend and DevOps work—contributing to widely used Google Cloud Dataproc projects such as initialization-actions and hadoop-connectors—with a strong emphasis on product quality and customer experience. Known for pragmatic engineering, he has improved cloud storage integrations, robustness of initialization scripts, and clarified user-facing error handling in open-source cloud tooling. Based in the Greater Paris area with a Computer Science degree from Texas Tech, he brings both leadership across cross-organizational teams and a knack for quietly fixing thorny interoperability and deployment issues that reduce friction for users.
11 years of coding experience
20 years of employment as a software developer
BS, Computer Science, BS, Computer Science at Texas Tech University
Stackoverflow
23reputation
1kreached
0answers
1question
Github Skills (22)
docker10
bash10
cloud-infrastructure10
hadoop10
dockers10
java10
gcp10
google-cloud-storage10
dataproc10
javas10
script10
system-administration10
error-handling10
rest-api8
oozie8
Programming languages (4)
Github contributions (5)
GoogleCloudDataproc/initialization-actions
Aug 2017 - Apr 2019
Run in all nodes of your cluster before the cluster starts - lets you customize your cluster
Role in this project:
DevOps Engineer
DevOps EngineerContributions:9 commits, 16 PRs, 9 pushes in 1 year 8 months
Contributions summary:Dan primarily contributes to the repository by implementing initialization actions for various tools used in the Google Cloud Dataproc environment. They've created initialization actions for Apache Livy, Apache Gobblin, and addressed a schema compatibility check for cloud-sql-proxy. The user also makes modifications to existing actions, such as fixing an issue with jackson jars for Oozie and improving docker pull retries. These actions focus on configuring and installing specific software packages within the Dataproc cluster environment.
nodesgoogle-cloud-dataprockubernetescustomizeterraform
GoogleCloudDataproc/hadoop-connectors
May 2015 - Jan 2019
Libraries and tools for interoperability between Hadoop-related open-source software and Google Cloud Platform.
Role in this project:Back-end Developer
Back-end DeveloperContributions:26 commits in 3 years 9 months
Contributions summary:Dan primarily contributed to the Google Cloud Dataproc Hadoop connectors library, focusing on enhancements to the Google Cloud Storage (GCS) integration. Their work included implementing direct upload options, handling GLOB expressions, validating bucket names, and exposing bucket creation options. The user also made modifications to error handling and improved user-facing error messages.
hadoop-filesystemgoogle-cloud-platformbigqueryhadoop-hcfsinteroperability
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