Top Skills for a Data Engineer

It’s not surprising that Data Engineers are in high demand. Their skills are greatly needed as companies deal with a deluge of data sources. And let’s face it...it’s not easy to acquire those skills.


You’ve got to prioritize the most important ones. But be smart about it too. Some skills require massive training and expertise--but if you know the shortcuts, you can accomplish in a few minutes what might otherwise take months.


The following chart provides a sampling of some of the top skills and responsibilities described in LinkedIn Blog Posts, as well as the associated tools, and available resources for quickly ramping up on those skills.


...and, we’ve also included a few shortcuts that allow you to expedite some of the more resource-intensive processes:

Skill

Tools

Sources for Education

Shortcuts

Build and maintain an enterprise data warehouse with cloud-based technologies

Snowflake, Amazon Redshift,

Google BigQuery, IBM Db2, Oracle Autonomous Data Warehouse


Cloud data storage

AWS, Azure, IBM Cloud

No shortcuts

Building and maintain critical ETL processes

Talend, SSIS, Panoply

Data Visualization

Tableau, PowerBI, Looker, Domo

Database design

SQL Server Database Modeler, Lucidchart

No shortcuts

Expertise in SQL

SQL Server, OracleDB, MySQL, DbSchema, Visual Paradigm

W3Schools--SQL Tutorial


Codecademy--LearnSQL

Scripting languages for ETL

Python, Perl, Bash

ETL skills are a HOT commodity...

You may have picked up on a few of our not-so-subtle hints that ETL is a big deal for data warehouse engineers.


ETL is a complicated, lengthy and messy process, and a lot can go wrong. And even the most passionate Data Engineer may wish that they could close their eyes and ‘make it go away’, and focus on more fun parts of the job.


Want to learn about how you can create data pipelines and virtual warehouses without ETL? Promethium can SHOW YOU HOW.

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