Augment Your In-house Data Team With LATAM Data Engineers
While the corporate world has been singing the “We live in the information age” song for quite a while now, the truth is that most businesses have, for a long time, limited the application of data analysis to sales and marketing departments only. However, over the last couple of years, data has gradually grown into a crucial tool for driving informed decision-making and improving day-to-day operations.
As a result, more and more executives have started investing in data analytics. For example, according to a 2023 HFS study, 70% of business leaders believe that proper data analytics is crucial for survival and top-line growth, while 72% view it as a critical factor in enhancing decision-making.
Amidst this revolution, a crucial yet often overlooked player has emerged – data engineers.
In this article, we’ll delve into data engineers’ invaluable contributions in transforming raw data into actionable insights and discuss why your business needs these professionals. We’ll also give a few tips on how to get the best data engineers in LATAM and offer a better solution for hiring these experts hassle-free.
According to Kevin Wylie, a data engineer who’s been on Netflix’s Content Data Science and Engineering team for over a decade, his primary mission is to “build beautifully simple data products for analytics engineers, data scientists, and analysts.” He further says that in any project he does, he’s always looking for ways to “make the lives of data consumers easier and to enable them to be more impactful.”
These two statements perfectly summarize the roles and responsibilities of data engineers — to help organizations build systems for collecting, validating, processing, and analyzing high-quality data to derive meaningful business insights. We can generally divide these roles into two broad categories: Data structure and management and Data analysis and insight generation.
Data Structure and Management | Data Analysis and Insight Generation |
Developing and managing data extraction, transformation, and loading tools to help organizations collect data from different source systems Identifying the organization’s data needs and identifying opportunities for data acquisition Building data pipelines and repository systems like warehouses and databases Crafting and enforcing data policies to ensure efficient data accessibility without jeopardizing data safety and privacy General maintenance of company data systems to enhance performance, reliability, and speed | Working alongside other data specialists to identify how to use existing data to enhance business processes Building, deploying, and maintaining data analysis tools and models Processing and organizing raw data Analyzing business data to identify trends and patterns Working with ML engineers to integrate ML programs into data systems for faster, real-time analysis Collaborating with business leaders and other data experts to identify how to enhance processes using derived insights |
As Kevin Wylie rightfully put it, the primary role of data engineers is creating and maintaining systems to make the lives of other data consumers (data scientists, analysts, and architects) easier. They can boost your existing data team’s productivity by handling distractive routine tasks and providing the necessary infrastructure for automating and expediting data collection, processing, and analysis.
Most data engineers currently wear several hats — they handle almost everything, from identifying organizations’ data needs to designing, deploying, and maintaining data systems. And reasonably so; several businesses are just realizing the importance of data engineering, and the demand for these experts outweighs the supply. However, with continuous investment in this sector, we’ll inevitably see the growth of specialization within data engineering teams.
Already, some engineers are categorizing themselves as generalists, pipeline-centric, or database-centric:
The global average data engineer’s salary is $119,494. If you already have an in-house data team, you might not see the value of hiring a data engineer and adding this hefty paycheck to your wage bill. Well, the truth is that data scientists are more than just an extra financial burden. In fact, their business benefits outweigh the expense by far.
Hiring data engineers is not just a luxury for the modern-day business — it’s a strategic investment that can significantly determine your survival and shape your growth. Here’s why:
IBM estimates that we create approximately 33 quintillion bytes of data each day. Unlike in the 1880s, when manual data analysis was the staple, this continuous increase in the amount of data generated daily makes it imperative for businesses to integrate engineering into their data processes. The old manual ways are no longer practical and are often prone to inaccuracies, high operation costs, and perennial delays.
By leveraging automation, data engineers help businesses navigate the influx of data volumes and the growing variety of data sources. They can create automated systems to streamline data collection, transformation, and analysis — enabling organizations to derive more accurate insights faster. These systems can also monitor data pipelines round-the-clock, identify issues, and proactively deploy remedies without human intervention, ensuring optimal performance.
Like oil, properly extracted, refined, and processed data can be a transformative asset that drives business Innovation and productivity. It can help business leaders better understand target customers, predict market trends, and make more informed production and marketing decisions. In fact, according to McKinsey, data-driven companies have 23 times higher chances of attracting new customers and are 19 times more likely to generate profits.
The irony is that despite these obvious benefits, only 24% of executives believe that their organizations are data-driven. Actually, studies show that most businesses do not use between 60% to 73% of their data.
Data engineers can help you increase your data collection and processing capacity and convert your business into a data-driven entity. They can create systems to enable you to take maximum advantage of your organization’s data, have a better insight into the market, and identify opportunities ahead of your competitors.
While hiring data engineers means extra paychecks, these professionals can also help your business reduce costs. First, they can design systems and algorithms to identify inefficiencies and bottlenecks in your operations, enabling you to optimize operational efficiency. In today’s fast-paced world, where downtime costs between $2,300 to $9,000 per minute, the fewer disruptions you have, the more you save.
Another way data engineers can help you is through supply chain optimization. By creating analytical systems to monitor and predict market trends, they can help you forecast product demands, ensuring you only stock goods on demand. This can help reduce holding costs and eliminate associated losses like expired products.
Do the following headlines ring a bell:
These are not fictitious headlines — they are real stories from reputable publications. As data becomes more integral to business processes, malicious cyber actors are continuously developing more sophisticated ways to compromise corporate data systems for personal gain.
While data engineers’ primary responsibility is creating systems for data collection, storage, and analysis, they are also responsible for ensuring the systems they develop are intrusion-proof. To this effect, they always work alongside cybersecurity experts in designing, building, deploying, and maintaining intrusion detection and prevention systems. Also, they can use their analytical expertise to create algorithms for detecting anomalies and flagging suspicious activities, enabling data security personnel to avert potential breaches.
Studies show that over 75% of businesses hiring engineers in the US are also seriously considering nearshoring to LATAM. Once known as the land of untapped potential, Latin America has gradually grown into a popular nearshoring destination over the last couple of years.
The region not only has a vast pool of high-quality data engineers but also offers several cost-saving opportunities. It also enjoys proximity, time zone alignment, and cultural similarities to North America and Canada and boasts a high English proficiency level and well-established remote working laws.
With the continuously rising demand for data engineering services in LATAM, finding the best data engineers in the region is increasingly becoming challenging. The competent ones are either already employed or interviewing for their next jobs.
So, how do you position your organization as a competitive employer to attract the best data engineering talent in LATAM?
Below are a few tips and steps to guide you through the hiring process:
Would you rather spend several weeks looking for the best data engineering service providers or get the work done for you as you focus on your priority tasks? Time is money. Let us help you save it by connecting you to the best data engineers in Latin America hassle-free.
At DevEngine, our expertise in helping organizations with staff augmentation, permanent placements, and building distributed teams is unmatched. We’ve assisted several companies like yours in hiring the best software and data engineering teams in LATAM since 2019. Whether you want one full-time data engineer, a complete distributed data engineering team, or a data engineering consultant for a short-term project, we have your back. Our record precedes us!
So, why should you list our services when hiring Latin American data engineers?
Are you ready to take advantage of LATAM’s vast pool of competent data engineers? Get In Touch With Us now for expert assistance.