Archive - Pipeline To Insights

Week 24/34: DevOps and DataOps Practices for Data Engineering Interviews

Building trustworthy, observable, and resilient data systems with the right mindset, culture, and tools.

Jun 15 •

7 key factors every Data Engineer Should Consider When Choosing Tools

What I wish I knew before choosing my Data Engineering Stack for my team

Jun 5 •

Week 23/34: Data Contracts for Data Engineerging Interviews

From theory to practice, how data contracts transform trust, ownership, and observability across the data engineering lifecycle

Jun 2 •

May 2025

Stop Being the Invisible Data Engineer: 8 Strategies for Career Success

Practical tips to grow your impact, visibility, and career as a data engineer.

May 29 •

Week 23/34: Real-Time Processing for Data Engineering Interviews

Understanding Real-Time Processing in Data Engineering with a hands-on implementation

May 25 •

How to Choose Between Batch and Stream Processing?

When to Use Batch vs Stream Processing: Key Differences, Use Cases, and Tools for Data Engineers

May 22 •

Semantic Models: Data Modelling for the Modern Data Stack

How Semantic Models work and how will they change our work

May 20 •

and

Week 22/34: Batch Processing for Data Engineering Interviews

Understanding Batch, Micro-Batch, and Near Real-Time Processing in Data Engineering

May 18 •

Proactive Mindset for Data Engineers

How to think beyond (data) pipelines and stay ahead of data problems?

May 13 •

Week 21/34: Open Table Formats for Data Engineering Interviews

What is Open Table Formats and their importance for data engineers

May 11 •

Week 20/34: Data Storage Paradigms for Data Engineering Interviews

Understanding Data Storage and its role in Data Engineering

May 6 •

dbt in Action #4: Snapshots and Slowly Changing Dimensions

Using dbt snapshots to track slowly changing dimensions, with a hands-on example.

May 4 •

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