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Books for Data Engineers

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dbt for Data Engineers

A Hands-On Case Study in Production-Grade Analytics Engineering

For the senior data engineer who already knows SQL, Python, and medallion architecture — and wants dbt's execution model and production trade-offs, not a syntax tutorial.

11 chapters · ~90,000 words · dbt-core 1.11 · hands-on case study

Status: in productionChapters 1–2 available freeWaitlist open

What you'll build

A single hands-on data platform (e-commerce domain), built progressively across all 11 chapters: customers, products, orders, order items, and payments, structured staging → intermediate → marts (Bronze / Silver / Gold).

Bronze

Raw sources: customers, products, orders, order items, payments.

Silver

Staging + intermediate: cleaned, cast, joined.

Gold

Marts: fct_order_items, fct_revenue, dim_product_scd2 and more.

This is for you if

  • ✓You run dbt in production and want the judgment calls, not the getting-started guide.
  • ✓You're fluent in SQL/Python/PySpark and can read a DAG without help.
  • ✓You want to know why a pattern changed, not just that it did.

Not for you if

  • —You're looking for a first introduction to SQL, CTEs, or data warehousing.
  • —You want dbt Cloud UI click-through instructions.
  • —You need inventory, shipping, or marketing-attribution domain coverage — this case study stays in customers/products/orders/order_items/payments.

Sample

Read chapters 1–2 free

The fundamentals and execution-model chapters are open to read now, in the same web edition buyers get.

Email signup opens soon. Until then, write to vincent@yzcworks.com.

Inside the web editionRead the sample

Contents & progress

Production ledger

Every chapter's real status — this book is written in the open.

ChTitleStatusCovers
01dbt Fundamentals: What It Is & How a Project RunsFree sampleWhat dbt is (and isn't), the ELT problem it solves, project anatomy, and how one run turns files into warehouse objects. A ground-up onboarding for readers new to dbt.
02dbt's Execution Model & Core ConceptsFree sampleThe DAG, compile vs. execute, sources and refs, materializations and adapter gaps.
03Project Structure & Layered ArchitectureOutlinedStaging/intermediate/marts conventions mapped onto Bronze/Silver/Gold, dbt_project.yml patterns.
04Testing & Data QualityOutlinedGeneric and singular tests, unit tests as TDD fixtures, source freshness as a quality gate.
05Incremental Models & Performance at ScaleOutlinedIncremental strategies, the microbatch pattern, partitioning and clustering per warehouse.
06Snapshots & SCD Type 2OutlinedSCD Type 2 via dbt snapshots, timestamp vs. check strategy, environment-aware config.
07Macros & Jinja for ReuseOutlinedJinja patterns for senior engineers, the package ecosystem, cross-project macros under dbt Mesh.
08Documentation & LineageOutlinedschema.yml docs, exposures, dbt Explorer, column-level lineage, the semantic layer.
09CI/CD & Deployment PatternsOutlinedSlim CI, state:modified+, dev/staging/prod environments, contract enforcement as a CI gate.
10Orchestration IntegrationOutlineddbt Cloud scheduler vs. external orchestrators, invocation patterns, retries and idempotency.
11Governance & Production OperationsOutlinedModel contracts, versioning, access modifiers, dbt Mesh, monitoring, incident runbooks.

Pricing

Pricing

Not yet available for purchase

Sales open when the book is finished. Waitlist subscribers get 30% off during launch week.

Standard Edition

$19.90 USD, one-time

The complete book and everything that ships with it.

  • —PDF + ePub + web (HTML) edition
  • —Templates & checklists pack
  • —Prompt pack for AI-assisted dbt work
  • —Free updates within this major version

Purchase not yet open

Join the waitlist

How delivery works

  1. 01Checkout is handled by Lemon Squeezy, which acts as the merchant of record and handles sales tax and VAT.
  2. 02Right after payment you get a receipt email with download links for every file. The web edition is a zipped HTML folder you open in any browser. The same files stay available from your Lemon Squeezy order page.
  3. 03The case-study code is a separate public repository under the MIT license, free for everyone. It opens at launch.
  4. 04Updates within this major version are uploaded to the same order, so you download them from the same place.

Buying for a team? Email vincent@yzcworks.com for a team licence. See the refund policy and terms.

Proof

Every example runs — check for yourself

The full case-study project will be a public, runnable repository under the MIT license. It opens at launch.

https://github.com/vincentyin-data/dbt-for-data-engineers-code

Vincent Yin

Senior Data Engineer

Vincent Yin is a senior data engineer with 18 years building data platforms across insurance and finance — enterprise data lakes, lakehouse migrations, dbt-modeled warehouses, and most recently production AI applications on the data stack. This series distills the judgment calls — not the syntax — that separate working pipelines from production-grade ones.

Refund policy & FAQ

30-day, no questions asked. Read the full policy.

Read chapters 1–2, free