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The Rise and Evolution of Data Engineering

written by Oliver Molander

It was in the early 2010s — almost exactly 10 years back — that the then-nascent term “data engineering” started to pop up in modern highly data-driven scaleups and fast-growing tech companies such as Facebook, Netflix, LinkedIn and Airbnb. As these companies harnessed massive amounts of real-time data that could provide high business value, software engineers at these companies had to develop tools, platforms and frameworks to manage all this data with speed, scalability and reliability. From this, the data engineer job started evolving to a role that transitioned away from using traditional ETL tooling to developing their own tooling to manage the increasing data volumes.

As big data evolved from a much-hyped boardroom buzzword to actually becoming reality, data engineering evolved in tandem to describe a type of software engineer who was obsessed about data; from data infrastructure to data warehousing, data modeling, data wrangling, and much more.

As Matt Turck notes in the latest Machine Learning, AI and Data Landscape analysis:

Today, cloud data warehouses (Snowflake, Amazon Redshift and Google BigQuery) and lakehouses (Databricks) provide the ability to store massive amounts of data in a way that’s useful, not completely cost-prohibitive and doesn’t require an army of very technical people to maintain. In other words, after all these years, it is now finally possible to store and process Big Data.

The cloud has grown into something very powerful when it comes to harnessing data. As noted by Zach Wilson: a lot of data engineering tasks that were cumbersome in the Hadoop world are simpler to do with tools like Snowflake or BigQuery. They allow you to do what took hundreds of lines of Java in dozens of lines of SQL.

As we’re finally realizing the true potential of big data beyond the hype, data engineers have become a hot commodity in any modern data-driven company no matter size — from startups and scaleups to large enterprises.

In addition to the highly quoted Dice’s 2020 tech jobs report — there’s plenty of statistics showing that the momentum for data engineering is palpable with no signals of stagnation.

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*Source: Validio

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