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Engineering Data Contracts: Schemas, SLAs, and Breaking‑Change Governance for Data Products
"Engineering Data Schemas, SLAs, and Breaking‑Change Governance for Data Products"
Data platforms rarely fail because the code “doesn’t work”—they fail because teams can’t agree on what the data means, what is guaranteed, and how change is managed without surprising downstream users. This book is written for experienced data and platform engineers, analytics engineers, and technical data product owners who need a rigorous, operational approach to making datasets and streams behave like reliable, evolvable interfaces.
You’ll learn to design data contracts as machine-checkable product specifying schemas and semantics, modeling time and late data, choosing appropriate schema formats, and distributing immutable contract artifacts through registries and catalogs. The book then goes deep on compatibility engineering and schema evolution, data SLIs/SLOs/SLAs and error budgets, and layered data quality assertions with producer- and consumer-driven contract tests. Finally, it details breaking-change governance with policy-as-code and CI/CD merge gates, plus the operational practices—observability, lineage, incident response, and postmortems—that keep contracts credible under real delivery pressure.
Readers should be comfortable with modern data architectures (batch, streaming, and warehouses) and collaborative software delivery. The differentiator is an end-to-end engineering not just what to document, but how to enforce, monitor, and govern change at scale.
Data platforms rarely fail because the code “doesn’t work”—they fail because teams can’t agree on what the data means, what is guaranteed, and how change is managed without surprising downstream users. This book is written for experienced data and platform engineers, analytics engineers, and technical data product owners who need a rigorous, operational approach to making datasets and streams behave like reliable, evolvable interfaces.
You’ll learn to design data contracts as machine-checkable product specifying schemas and semantics, modeling time and late data, choosing appropriate schema formats, and distributing immutable contract artifacts through registries and catalogs. The book then goes deep on compatibility engineering and schema evolution, data SLIs/SLOs/SLAs and error budgets, and layered data quality assertions with producer- and consumer-driven contract tests. Finally, it details breaking-change governance with policy-as-code and CI/CD merge gates, plus the operational practices—observability, lineage, incident response, and postmortems—that keep contracts credible under real delivery pressure.
Readers should be comfortable with modern data architectures (batch, streaming, and warehouses) and collaborative software delivery. The differentiator is an end-to-end engineering not just what to document, but how to enforce, monitor, and govern change at scale.
519 pages, Kindle Edition
Published March 8, 2026
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