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Achievements

Achievement: Galaxy BrainAchievement: Pair ExtraordinaireAchievement: YOLOAchievement: QuickdrawAchievement: Public SponsorAchievement: Pull Sharkx2

Achievements

Achievement: Galaxy BrainAchievement: Pair ExtraordinaireAchievement: YOLOAchievement: QuickdrawAchievement: Public SponsorAchievement: Pull Sharkx2

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JeonDaehong/README.md
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Hello! My name is Daehong Jeon
I'm Software Engineer / Data Engineer.


My Blog
Blog
 My Email
Email
 My Linkedin
Linkedin

🧑‍💻 About Me

💻 Data Platform & Lakehouse Engineer

  • Extensive experience in the finance and e-commerce domains, covering everything from Hadoop-based ecosystems to modern cloud-native data platforms.
  • Skilled in processing tens to hundreds of terabytes of data, developing Spark-based distributed ETL pipelines, optimizing Hadoop legacy systems, and designing highly available, failover-ready, and concurrency-controlled data infrastructures.
  • Experienced in designing and building Data Lakehouse architectures, operating large-scale Amazon Redshift-based Data Warehouses, and developing production-grade ETL orchestration with Apache Airflow.
  • Hands-on experience in metadata management, data governance, workflow automation, platform reliability, and large-scale data platform operations.
  • Designed and implemented OWL ontology-based Virtual Knowledge Graph (VKG) architectures for semantic data integration and knowledge-driven analytics.

👥 Leadership & Management

  • Experience leading data platform projects from architecture design to production operation, while coordinating stakeholders and driving technical decision-making.
  • Actively involved in mentoring, knowledge sharing, technical leadership, and improving engineering productivity through automation and operational excellence.

🌐 I love contributing to open source

  • Active contributor to data engineering projects such as Apache Iceberg and Apache Kafka, including issue triage, bug investigation, PR reviews, and documentation improvements.
  • Open Source Mentoring (2025.05~) — Engaged in fostering a healthy and sustainable open source culture in Korea.

🎯 My Goals

  • To grow as a technology leader who continuously adopts and disseminates emerging technologies while building strong engineering cultures.
  • To design and operate scalable, reliable, and maintainable data platforms that support high-volume, mission-critical workloads.
  • To contribute to both business success and the open source ecosystem through technical excellence, leadership, and knowledge sharing.

🛠️ Open Source Contributions

⭐️ Contribution Library

Apache Iceberg Apache Iceberg Rust Apache Paimon Rust Spring Kafka Apache Gravitino

⭐️⭐️ Contribution & Activity List

Project Summary Type Link Date
Optimized delete row selection using deleted ranges instead of per-position iteration, improving read performance by up to 48% for contiguous deletes. Performance Improvement (Core) PR 26.10
Fixed FLOAT/DOUBLE comparison inconsistencies with Java, improving partition filtering and statistics correctness. Bug Fix, Core PR 26.10
Cached typed columns in SortMergeCursor to reduce repeated lookups and improve merge performance. Performance Improvement (Core) PR 26.10
Reused buffers and merge rows to reduce allocations during sort-merge reads. Performance Improvement (Core) PR 26.10
Optimized deletion-vector range generation using Roaring Bitmap runs. Performance Improvement (Core) PR 26.10
Aligned FLOAT/DOUBLE partition value formatting with iceberg-java. Bug Fix, Core PR 26.10
Optimized vectorized position-delete checks with range-based index traversal. Performance Improvement (Core) PR 26.09
Backported vectorized position-delete optimizations to Spark 3.5, 4.0 and 4.1. Improvement (Core) PR 26.09
Fixed Markdown formatting in the Row-level Deletes documentation. Docs PR 25.09
Fixed missing superclass validation in OAuth2 token response validation. Bug Fix PR 25.09
Fixed incorrect field assignments in metadata service tests. Bug Fix, Test PR 25.08
Documented Flink table maintenance operations. Docs PR 25.08
Fixed group updates that incorrectly skipped non-role changes. Bug Fix, Test PR 25.08
Fixed null handling in EntityCombinedFileset. Bug Fix, Test PR 25.08
Fixed null-safe handling of the managed property. Bug Fix, Test PR 25.08
Added request validation for partition operations. Improvement PR 25.08
Migrated Flink catalog tests from JUnit 4 to JUnit 5. Improvement (Core) PR 25.05
Backported the JUnit 5 migration to Iceberg 1.19 and 1.20. Improvement (Core) PR 25.05
Updated Kafka retry topic template tests and documentation. Improvement, Docs PR 24.10

💡 Tech Stack

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  1. study-java-algorithm study-java-algorithm Public

    Java 1

  2. iceberg-dv-anatomy iceberg-dv-anatomy Public

    Python 2

  3. apache-spark apache-spark Public

    Forked from apache/spark

    Apache Spark - A unified analytics engine for large-scale data processing

    Scala 1

  4. gravitino gravitino Public

    Forked from apache/gravitino

    World's most powerful open data catalog for building a high-performance, geo-distributed and federated metadata lake.

    Java 1

  5. iceberg iceberg Public

    Forked from apache/iceberg

    Apache Iceberg

    Java 1

  6. iceberg-rust iceberg-rust Public

    Forked from apache/iceberg-rust

    Apache Iceberg Rust

    Rust 1