6 Responsibilities of a Data Engineer

Unclear data engineering job description ? Wondering what responsibilities falls within a data team ? Then this post is for you. In this post we go over the 6 key responsibilities of a data engineer. The number of these responsibilities that you may end up handling depends on your company and team. Teams in smaller companies generally handle all 6 responsibilities, whereas larger sized companies may have individual(or multiple) teams handling one(or a mix) of these responsibilities.

6 Key Concepts, to Master Window Functions

In this post, we go over 6 key concepts to help you master window functions. Window functions are one the most powerful features of SQL, they are very useful in analytics and performing operations that cannot be done easily with the standard group by, subquery and filters. Despite this, window functions are not used frequently. If you have ever thought 'window functions are confusing', then this post is for you.

What are Common Table Expressions(CTEs) and when to use them?

You have heard of Common Table Expressions(CTEs), but are not be sure what they are and when to use them. What if you knew exactly what Common Table Expressions(CTEs) were and when to use them? In this post, we go over what CTEs are, and their performance comparisons against subqueries, derived tables, and temp tables to help decide when to use them.

Whats the difference between ETL & ELT?

This post goes over what the ETL and ELT data pipeline paradigms are. It tries to address the inconsistency in naming conventions and how to understand what they really mean. Finally ends with a comparison of the 2 paradigms and how to use these concepts to build efficient and scalable data pipelines.

How to add tests to your data pipelines

Trying to incorporate testing in a data pipeline? This post is for you. In this post, we go over 4 types of tests to add to your data pipeline to ensure high-quality data. We also go over how to prioritize adding these tests, while developing new features.

10 Skills to Ace Your Data Engineering Interviews

Preparing for a data engineering interview and are overwhelmed by all the tools and concepts?. Then this post is for you, in this post we go over the most common tools and concepts you need to know to ace your data engineering interviews.

What is a staging area?

Wondering what is staging and why you need one for your data pipelines? Then this post is for you. In this post, we will go over what exactly a staging area is and why it is crucial for data pipelines.

What is a Data Warehouse?

Unclear what a data warehouse is or when to use one? Then this post is for you. In this post, we go over what a data warehouse is, the need for it, and the differences between using an OLTP and OLAP database as a data warehouse.

How to Scale Your Data Pipelines

Confused by all the tools and frameworks available to scale your data pipeline? Then this post is for you. In this post, we go over what scaling is, the different types of scaling, and how to choose scaling strategies for your data pipelines. By the end of this post, you will be able to come up with the correct scaling strategy for any data pipeline.

Understand & Deliver on Your Data Engineering Task

Want to deliver on your data engineering tasks with confidence? Then this post is for you. In this post, we go over a list of steps that you can use to understand what your assigned work is, why it matters and how to deliver great work.