dbt (data build tool) interview questions

What Is DBT and Why Is It So Popular – Intro To Data Infrastructure Part 3

Interviews for Top Jobs at dbt Labs

Software Engineer Interview

Marketing Interview

11. How do I use the incremental materialization? incremental models are defined with select statements, with the the materialization defined in a config block. {{ config( materialized=’incremental’ ) }} select … To use incremental models, you also need to tell dbt, on how to filter the rows on an incremental run and the uniqueness constraint of the model (if any).

38. How do I run models downstream of one source? To run models downstream of a source, use the source: selector: $ dbt run –models source:jaffle_shop+

40. How do I specify column types? Simply cast the column to the correct type in your model: select id, created::timestamp as created from some_other_table

14. What is the is_incremental() macro ? The is_incremental() macro will return True if: the destination table already exists in the database dbt is not running in full-refresh mode the running model is configured with materialized=’incremental’

24. What is the difference between dbt Core, the dbt CLI and dbt Cloud? dbt Core is the software that takes a dbt project (.sql and .yml files) and a command and then creates tables/views in your warehouse. dbt Core includes a command line interface (CLI) so that users can execute dbt commands using a terminal program. dbt Core is open source and free to use. dbt Cloud is an application that helps teams use dbt. dbt Cloud provides a web-based IDE to develop dbt projects, a purpose-built scheduler, and a way to share dbt documentation with your team. dbt Cloud offers a number of features for free, as well as additional features in paid tiers

Why are companies hiring analytics engineers? #

It’s still common for data engineers to own 100% of the ETL process in an organization, although this is often a legacy organizational structure from the time when data warehouses weren’t fast enough to allow for data transformation to be done in-warehouse. If you’re using a modern data warehouse, this approach is no longer best practice. For modern data teams, the ideal setup is for analysts, who have a much better understanding of the business logic that goes into data transformation, to own most or all of the transformation process.

An analytics engineer can be that seamless bridge that connects data analysis to data engineering. This role is often the difference between analysts being empowered to turn their work around in real-time vs. needing to wait in the queue to get data engineering support. It is not uncommon for that difference to result in a 10x in the velocity of the analytical process.

Data quality can erode in a few places during the transformation process as an organization matures. Without a tight process, this code can often become full of copy-paste, tables that are no longer used still stick around and create confusion, errors creep in without anyone realizing it, and performance can degrade. All of these issues are simply a byproduct of entropy—the natural state of the world is to degrade towards disorder—and they’ll slow down your team’s productivity significantly.

When data engineers own data transformation, quality erodes because they often don’t quite have the depth of understanding of the business needs that data analysts have. Things get lost in translation, and data engineers aren’t actually able to identify what constitutes an “error state” in the data.

The analytics engineer improves data quality by bringing a deep understanding of what the business needs into the transformation process, but also by bringing the rigor of software engineering to analytics code.

In some cases, the need for an analytics engineer comes from the fact that organizations are invested in specific tools and workflows. dbt is a tool that is designed to allow analysts to own the entire analytics engineering workflow. Once companies adopt dbt, they start hiring to match that need.

How to answer “why do you want this job” interview question

Answering this interview question can be a surprisingly tricky one, especially if you try to answer it without thinking about who your audience is and what they really want to know. If you want to learn how best to answer this question, you will need to consider both the needs of the company and your own career goals.

When asked the interview question “Why do you w…

Read more at Why Do You Want This Job?

“What is your greatest strength?” may seem like an easy job interview question. However, for many candidates it can be tricky—either theyre too modest in their response or they dont highlight those strengths that most closely match the job requirements. Many candidates are unsure about how to answer this question. It’s important to be prepared for this question and have an answer ready. Even if you aren’t asked this question, you will be aware of your strengths and what you can bring to the position.

In this article, youll find a guide on how to answer the interview question about your greatest strengths, and what—and what not—to say when you respond, with example answers too.

FAQ

Is dbt a ETL tool?

What is dbt tool used for?

What are the SQL interview questions?

• What is Database? …
• What is DBMS? …
• What is RDBMS? …
• What is SQL? …
• What is the difference between SQL and MySQL? …
• What are Tables and Fields? …
• What are Constraints in SQL? …
• What is a Primary Key?

Is dbt a good tool?