Modern data pipelines give your data engineers the opportunity to pursue higher-value activities.
Data engineers are extremely talented individuals whose abilities are often squandered manually building data pipelines to extract, transform and load data. Even when utilising classic ETL tools, companies often have to assign teams of high-value staff to maintain and configure those tools.
By definition, a tool should "aid in accomplishing a task." However, more often than not, classic ETL tools drain the time and enthusiasm of data engineers. Rather than enabling data engineers to thrive, they demand maintenance and attention in a manner akin to leaking pipes — pipes down which companies pour money — with little to show in return.
In a previous blog post, we crunched the numbers to determine whether it's best to build or buy a data pipeline. From all angles, it makes sense to buy a modern data pipeline tool.
One angle is the cost of building your own data connectors. Cost varies across region and salary scale, but you can make some quick calculations of the engineering time spent building and maintaining connectors and the total cost of ownership for your organisation. The monetary cost will likely meet or exceed six figures, to say nothing of the costs imposed by downtime.
The talent and ability of data engineers constitute a business opportunity: Here is a capable workforce prepared to lead future technology advancements and drive growth. Instead of building data pipelines for common data sources, your engineers could build integrations for obscure and unsupported sources. More importantly, they could help your data scientists build the infrastructure to support machine learning models, automated decision-making, and other high-value activities.
As the volume of data increases, so too does the demand for data engineers. Economics’ founding law of supply and demand has pushed data engineers’ salaries as high as €125,000 per year. With engineering salaries growing, companies must accept that there is no return on investment in building data pipelines.
More importantly, organisations need to consider staff morale. Talk to your data engineers. Ask them how they feel about painstakingly building and monotonously maintaining data pipelines. Ask them what positive change they could bring to the data function and the organisation as a whole if their time was liberated by automated data pipelines.
Discover how to free some of your most technically talented people to deliver a positive return for your company. Talk to them, then talk to us at email@example.com.
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