Day 1 · October 6
Practical Big Data Engineering
The infrastructure, pipelines, and platforms that power data-driven organizations. We’re looking for war stories from the engine room – architecture decisions, scaling challenges, performance wins, and the migrations nobody wanted but everyone needed.
- Production data pipeline architectures
- Lakehouse & data mesh in practice
- Stream processing at scale (Kafka, Flink, Spark)
- Data quality & observability in production
- Cost optimization for cloud data platforms
- DataOps & CI/CD for data workflows
- Real-time analytics systems
- Data governance that actually works
- Legacy warehouse modernization
- Open table formats (Iceberg, Delta, Hudi)
- Performance tuning & query optimization
- IoT data ingestion & edge processing
- Internal data platforms & self-service tooling
- Multi-cloud & hybrid data architectures