A design pattern is a reusable, technology-agnostic solution to a recurring problem, describing the trade-offs, structure, and reasoning for how to approach something so you can apply it across different situations. A definition simply states what a term means—it establishes shared vocabulary and meaning without prescribing how to solve a problem. In short: a definition tells you what something is, while a design pattern tells you how to do something well and why.
Design patterns support the way of working in Data Engineering 2026 and are applied in the data-solution-2026 proof of concept.
Patterns are grouped under Data engineering (data objects, extractors, layers, temporal storage) and Generic (orchestration, decomposition, simplicity, and separating specification from implementation). Generic patterns apply outside data platforms; data-engineering patterns name concepts used in data solutions.
The main reasons to document patterns this way are:
- They can be used as blueprints for AI generation of underlying code in any language or tool. Select the patterns you need for your data solution.
- They provide a vocabulary to discuss frameworks, tools, platforms, and data solutions—and to compare them.
- They help you design a technology-agnostic data solution that is more robust to technology changes.
Defining and documenting design patterns is inherently complex. Patterns evolve as practices, tools, and teams change; no catalog is ever finished on the first pass. Treat the content in this repository as a living reference: expect ongoing refactoring, clarification, and improvement rather than a fixed specification. Contributions, corrections, and sharper wording are welcome.
- Data Engineering Design Patterns
- Definitions
- Design patterns
- Data engineering
- Data extractor
- Data object container
- Data object contract
- Data object poller
- Data object quality of service
- Data object quality
- Data object refresh contract
- Data object tree property inheritance
- Data object tree
- Data object
- Data solution layer
- Data solution
- Event-based orchestration
- Historic bitemporal table
- Generic
- Data engineering
- Implementation
- Data Object Refresh Contract
- Event Based Orchestration
- Related repositories
- Data Engineering 2026 — Course and learning materials
- Data Solution 2026 — Data solution proof of concept