A Merkle Tree is a scalable, SQL-friendly approach to verifying data integrity — widely used in systems like Git, blockchains, and distributed databases.

Design principles like SOLID, DRY, KISS, YAGNI, and GRASP aren’t rules — they’re tools for managing complexity, preserving clarity, and making software resilient to change. This deep dive explores each principle with real-world examples and refactoring patterns.

Slowly Changing Dimensions (SCD) are essential for maintaining historical accuracy in data systems where context evolves over time. This in-depth guide explores all SCD types, their engineering trade-offs, and practical strategies for designing dimensional data that preserves meaning — not just metrics.

Attribution across channels and devices isn’t just about tracking—it’s about understanding synergy across traffic sources like push notifications, social media, webinars, and affiliate programs. Combining data-driven attribution with MMM and incrementality testing enables smarter budget decisions under modern privacy constraints.

Modern data engineering isn’t about building pipelines — it’s about building trust, reliability, and cost-aware systems. This article reframes the role and explains what experienced engineers actually do.