Data Engineering Frameworks
Downloadable, reusable architecture and operating frameworks for modern data and AI platforms. Adapt as-is or plug in your organization values.
Real-Time Streaming Data Platform Framework
Streaming platform framework covering Kafka/Kinesis ingestion, schema registry, stream processing, serving layers, and end-to-end observability for real-time analytics.
Enterprise Data Governance Operating Model
Practical governance operating model with RACI matrices, data stewardship, catalog standards, classification tiers, access reviews, and change management workflows.
AI-Ready Data Platform Framework
Reference framework for building AI-ready data platforms — feature stores, vector/RAG pipelines, LLM governance, model lineage, and MLOps integration patterns.
Medallion Lakehouse Architecture
Reference architecture for bronze/silver/gold medallion lakehouse on AWS and Snowflake — zone definitions, ingestion patterns, transformation standards, and consumption SLAs.
Data Quality Engineering Framework
End-to-end operating framework for data quality in modern DE teams — dimensions, rule taxonomy, execution layers, ownership, escalation paths, and KPI scorecards.
Data Mesh on AWS with Lake Formation
Complete implementation framework for domain-oriented data mesh on AWS — Lake Formation federated governance, cross-account data products, domain ownership, and phased rollout.