Daniel Weeks

Co Founder, CTO @ Tabular

About Daniel Weeks

Dan Weeks CTO at Apache Iceberg

Dan Weeks serves as the Chief Technology Officer (CTO) and is a Project Management Committee (PMC) Member at Apache Iceberg. He has been instrumental in the development and growth of Apache Iceberg, a high-performance table format for large analytic datasets. His role encompasses overseeing the technical roadmap and contributing to the project's long-term vision.

Contribution to Apache Iceberg at Netflix

Dan Weeks co-created Apache Iceberg while working at Netflix. In his tenure at Netflix, he led the Big Data Compute team, focusing on the development of a new table format designed to handle complex big data challenges. The aim was to provide a robust solution for data management that supports transactional consistency and schema evolution.

Focus on Data Platform Productivity

Dan Weeks is deeply committed to enhancing productivity within data platforms. He works on solving critical issues related to data correctness, performance, and reducing costly distractions. By contributing to the development of features like ACID transactions and schema evolution in Apache Iceberg, he supports the efficient and reliable processing of data.

Innovations in Data Management with Apache Iceberg

Under the guidance of Dan Weeks, Apache Iceberg has incorporated advanced features like hidden partitioning, time travel, MERGE operations, branching, tagging, in-place table evolution, and metadata indexing. These innovations address key challenges in data management and make Iceberg a powerful tool for managing large datasets with SQL behavior.

Vision for Modular Data Architecture

Dan Weeks envisions a future where data platforms benefit from a modular data architecture enabled by Apache Iceberg. He believes that such an architecture enhances productivity by allowing for scalable, maintainable, and efficient data management solutions. His efforts are geared towards making Iceberg an open standard for tables, providing a cohesive framework for SQL-based data operations.

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