Thinking Like a Data Engineer Framework 🤔
Joe Reis' guide to Developing a Data Engineer Mindset
As a data engineer, your role involves sourcing raw data, transforming it into valuable insights, and making it accessible for downstream use cases.
introduced a framework in his Data Engineering course on Coursera/DeepLearning.AI that helps you think like a data engineer. 🙂
𝟭. Understand Business Goals: Understand business goals and stakeholder needs, identify gaps in current systems, and define how data will be used.
𝟮. Define Requirements: Convert stakeholder needs into functional (what the system does) and non-functional (technical specifications) requirements, then confirm with stakeholders.
𝟯. Tool/Technology Selection:
Choose tools and technologies based on a cost-benefit analysis that best meets the system’s requirements.
Build and test a prototype to ensure it meets expectations. Iterate based on feedback before full production.
𝟰. Build & Deploy: Implement, monitor, and continuously improve the system as needs evolve or new technologies emerge.
This framework isn't a one-time process; it's iterative. As business goals evolve, stakeholder needs shift and technology advances, data engineers must continuously evaluate and improve data systems to stay aligned with the changing landscape.
If you're interested in learning more about this framework, check out Joe’s course [here].
Want to learn more about Joe Reis?
Substack: [Joe Reis’s Substack Link]📝
Book: Fundamentals of Data Engineering: Plan and Build Robust Data Systems by Joe Reis and Matt Housley – [Amazon Australia Link Here]📚
Course: Data Engineering – [DeepLearning.AI]🧑🎓
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