Chethan U
Stony Stratford, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolChethan U is a cloud-native data engineer with 10 years' experience building and architecting big data pipelines using Apache Beam, Flink, Spark, Kafka, Airflow and Trino on Kubernetes. Based in Stony Stratford, he blends hands-on DevOps work—contributing initialization actions for Google Cloud Dataproc and upgrading critical components like Livy, Spark NLP and Presto—with data engineering contributions to Apache Airflow, migrating and standardizing example DAGs across many providers. He is comfortable across the stack from orchestration to ML (TF.Keras, PySpark.ML) and has a track record of making distributed systems more configurable and maintainable. Colleagues would note his focus on practical, production-ready integrations and a habit of updating foundational tooling to keep clusters and pipelines current.
10 years of coding experience
A, A at M S Ramaiah Bangalore
English, Hindi, Kannada
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (21)
apache-airflow10
google-cloud-dataproc10
python10
data-engineering10
bash10
workflow-engine10
orchestration10
data-pipeline10
presto10
data-integration10
cloud-computing9
alluxio9
infrastructure-as-code9
etl9
docker8
Programming languages (17)
Github contributions (5)
apache/airflow
Jul 2019 - Dec 2022
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Role in this project:
Data Engineer
Data EngineerContributions:17 reviews, 59 PRs, 46 comments in 3 years 6 months
Contributions summary:Chethan's commits primarily focused on migrating example DAGs for various providers (Trino, Zendesk, JDBC, Jenkins, MSSQL, MySQL, Opsgenie, Presto, Plexus, SQLite, Telegram, Tableau, Salesforce, Asana, Neo4j, Postgres, Snowflake, Qubole, Azure, WinRM, Influx, DingTalk, CNCF Kubernetes, Alibaba, Singularity, Dbt, Databricks, Hive, Kylin, Drill, Druid, Cassandra, Spark, Pig, GitHub, LevelDB, Slack, Redshift, Airbyte) to a new design within the Apache Airflow project. This involved updating example DAGs to align with the project's architectural standards. The work suggests a focus on maintaining and improving the project's examples for various integrations.
monitorpythonschedulerapacheprogrammatically
GoogleCloudDataproc/initialization-actions
Jul 2019 - Apr 2020
Run in all nodes of your cluster before the cluster starts - lets you customize your cluster
Role in this project:DevOps Engineer & Cloud Engineer
DevOps Engineer & Cloud EngineerContributions:6 commits, 13 PRs, 66 comments in 9 months
Contributions summary:Chethan primarily focused on updating and configuring various initialization actions for Google Cloud Dataproc clusters. Their contributions included updating Livy to version 0.6.0, configuring additional connectors for Starburst Presto and Presto, updating Spark NLP to the latest version, adding options to configure Presto and Starburst Presto server ports, and bumping the default Alluxio version. The user also updated Presto to v332.
nodesgoogle-cloud-dataprockubernetescustomizeterraform
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