Lead Senior Recruiter
Data, Insight & Analytics
View profileWelcome back to my Analytics Engineering series! So far, we’ve looked at what analytics engineering is and why this role is taking centre stage in the modern data stack. Now, we’re talking about the skills and tools every analytics engineer (AE) should have in their skillset.
Whether you’re a Data Professional looking to break into the field or a company building a best-in-class data team, understanding these skills and tools is important!
Analytics engineers are a unique blend of engineer, analyst, and storyteller. Their skill set shows this too, with a blend of tools like:
Strong SQL Skills
Data Transformation Expertise
Familiarity with the Modern Data Stack
Software Engineering Principles
Communication and Business Acumen
Now that we’ve covered the key skills, let’s spotlight the tools every AE should know. These tools are the backbone of the modern data stack.
DBT (Data Build Tool)
Cloud Data Warehouses
BI Tools
How These Skills and Tools Benefit Teams
For Data Professionals:
Mastering these skills and tools opens doors to exciting opportunities. Analytics engineering is one of the most in-demand, high-impact roles in data today.
For Employers:
A well-equipped AE ensures your data infrastructure is solid and scalable. They’ll help you move faster, reduce errors, and unlock the full potential of your data.
Final Thoughts
Analytics engineering is all about combining technical expertise with business insight. By mastering key skills like SQL and data modelling and using tools like DBT and Snowflake, analytics engineers can transform raw data into a strategic asset.
In the next article, I’ll discuss the future of analytics engineering and what’s on the horizon for this exciting field. Whether you’re a data professional or employer, the world of analytics engineering offers endless possibilities. I’m happy to help with any growth needed in your team!