David Zhang
Employers on the program
- 2024–2026Amazon Web Services4 talks
Appearances by year
- AWS re:Invent
Talks
| Date | Event | Conference | Role | Title | Links |
|---|---|---|---|---|---|
| Nov 30, 2026 | AWS re:Invent 2026 | AWS re:Invent | breakout | Accelerating data analytics on Apache Iceberg with Amazon S3 Tables as Amazon Every analytics query starts with how your data is stored. In this session, learn how Amazon S3 Tables deliver purpose-built Iceberg table storage that…Show lessEvery analytics query starts with how your data is stored. In this session, learn how Amazon S3 Tables deliver purpose-built Iceberg table storage that accelerates query performance, reduces storage costs, and eliminates table maintenance overhead. | |
| Nov 30, 2026 | AWS re:Invent 2026 | AWS re:Invent | chalk talk | Simplify Data Analytics operations with AI-powered Apache Spark agents on AWS as Amazon Running analytics workloads at scale carries a hidden operational tax: teams commonly lose significant engineering time to debugging failures, leave performance…Show lessRunning analytics workloads at scale carries a hidden operational tax: teams commonly lose significant engineering time to debugging failures, leave performance and cost improvements on the table, and spend months on each version upgrade. | |
| Dec 1, 2025 | AWS re:Invent 2025 | AWS re:Invent | builders session | Build high performance Apache Iceberg data lakes with Amazon S3 Tables [REPEAT] as Amazon Master the art of building high-performance Apache Iceberg data lakes for real-world use cases using Amazon S3 tables. | |
| Dec 2, 2024 | AWS re:Invent 2024 | AWS re:Invent | chalk talk | Using natural language to author data integration applications as Amazon In this chalk talk, learn how users of all skill levels, including data engineers, ETL developers, and business users, can use the latest generative AI…Show lessIn this chalk talk, learn how users of all skill levels, including data engineers, ETL developers, and business users, can use the latest generative AI capabilities to onboard, author, and tune data integration applications using natural language, without needing in-depth knowledge of the underlying systems. |
Frequent co-speakers
| Speaker | Shared events | Shared talks | Last together |
|---|---|---|---|
| Satesh Sonti | 3 | 1 | 2026 |
| Aaron Chen | 3 | — | 2026 |
| Aaron Sempf | 3 | — | 2026 |
| Aarthi Raju | 3 | — | 2026 |
| Abbas Mooraj | 3 | — | 2026 |
| Abhijeet Jangam | 3 | — | 2026 |
| Abhishek Pandey | 3 | — | 2026 |
| Abhishek Sharma | 3 | — | 2026 |
| Abhishek Srivastav | 3 | — | 2026 |
| Abilashkumar P C | 3 | — | 2026 |
| Adam Hill | 3 | — | 2026 |
| Adam Richter | 3 | — | 2026 |
| Addy Upreti | 3 | — | 2026 |
| Aditi Garg | 3 | — | 2026 |
| Aditya Challa | 3 | — | 2026 |
Speakers with the same name are merged into one entry, so this page may combine more than one person. Affiliations are shown as each conference listed them.