At this point in time, data has become an essential factor in our lives.
As we progress further in 2025, it is clear that data is the underpinning of success for businesses courtesy to the astonishing amount of information being created on a daily basis, which amounts to around 402.74 million terabytes. This explains the high demand for data engineers who are essentially the “architects” of the data systems. With their ability to design and maintain systems, they’re able to manage massive amounts of information.
Even so, there has been a shortage of skilled professionals. The question is, how can businesses build an effective data engineering team when there is an alarming shortage of talent, and it is so difficult to find skilled staff? Let us deep dive.
Why is the Demand for Data Engineers Increasing Rapidly?
According to Bureau of Labour Statistics, IT jobs are expected to grow at a shocking above average rate of 356,700 jobs a year for the next decade. This unsurprisingly results in an increase in data engineering jobs. On top of that, the data engineering market is estimated to grow at a rate of 17.6% every year reaching a total market value of USD 240.60 billion by the end of the decade.
Surprisingly, between the years 2021 and 2022, data engineering was recognized as one of the fastest growing tech fields with 100% growth, which is why it is no surprise that in 2023, data engineers started flooding the market.
Data engineers are crucial for the management and maintenance of infrastructure required to facilitate analytics and AI. The race to harness AI, machine learning, and real-time analytics has created a crazy demand for elite data engineers. It is getting even worse for skilled workers with all industries in finance, healthcare, and e-commerce undergoing digital transformations. Companies now require individuals that can build scalable data pipelines from heterogeneous sources of data with high data quality.
A report by Lepaya suggests, 83% of HR leaders think the demands of the workforce are growing quicker than the abilities of the employees and the major reason is technology. For example, a 2020 survey discovered that 69% of employers had difficulties filling open positions due to a shortage of qualified personnel particularly for IT, data analytics, and engineering roles. In the same report, 52% of hiring managers also considered skill gap as a major issue during the recruiting process. This is the main reason for businesses to approach tech staffing agencies.
According to SIA, revenue from the US tech staffing market grew 17% in 2021 and 16% in 2022.
Technology staffing companies have profound knowledge of the industry and comprehend the ever-changing skills needed in the competitive tech world. This allows them to evaluate an
applicant’s skills based on their technical abilities, adaptability to new trends, and soft skills such as communication and collaboration. With their expertise, staffing agencies guarantee that businesses receive workers who not only meet current job capabilities, but also grow with technology.
Essential Skills for Data Engineers: Key Competencies for 2025
The field of data engineering is greatly changing, and that means everyone working in the industry must possess technical skills, creativity, and flexibility to tackle challenges. It is imperative that data engineers evolve with technology and his existing skill set by 2025. Below are the primary skills that the leading data engineers of 2025 will need to hone:
1. Automation
An IDC study is forecasting that automation will start entering data engineering as early as 2026 due to the fact that 75% of data engineering workflows will be somewhat automated. To meet evolving data needs, automation is vital in the workplace. Data engineers are expected to be adept with an increasing number of performance enhancing tools such as Apache Airflow, Terraform, Kubernetes, Docker, Kafka, etc.
2. Cloud Computing
According to Indeed, newly created postings for data engineering positions have increased by a staggering 35% annually. This emphasizes the demand for specialized data engineering positions. With the growing need for a more nuanced approach to data engineering, cloud data engineering emerged as one of the most critical areas.
The DaaS market is expected to grow from USD 5.4 billion in 2023 to USD 13.2 billion in 2026. This sharp increase highlights the growing demand for cloud-based data engineering services that are both scalable and flexible.
It is now considered one of the core competencies of data engineers to understand AWS, Azure, and Google Cloud because they allow for building flexible and scalable data infrastructure. In fact, the same indeed report shows that Azure is mentioned in 75% of job ads, with AWS coming second at 49.5% and then Google Cloud Platform at 21.3%.
3. Data Warehousing
The businesses and organizations dealing with reporting, analytics, and AI-based decision-making solutions require structured storage systems as their core skill. This makes data warehousing a key concern for the data engineers. Over the period, as the businesses are moving to cloud solutions, the revenue for the cloud data warehouse market is projected to increase up to USD 33.2 billion by 2027.
Learning modern data warehouse concepts such as those offered by Snowflake, BigQuery, and Amazon Redshift is crucial for efficiently working with large datasets. Engineers should also implement schemas and be knowledgeable regarding partitioning, indexing, and query optimization to guarantee performance and cost efficiency. The ability to manage structured and unstructured data using Lakehouse architectures, such as Delta Lake, Apache Iceberg, and Hudi, is also critical. With increasing popularity of real-time analytics, data engineers are also required to load streaming data into warehouses while ensuring security and governance compliance.
Real-time data processing is crucial in the modern world, especially to data engineers! A collaborative survey conducted by Forbes Insights and TIBCO Software says that 70 percent of companies struggle with the fact that they do not have access to real-time analytics. In processes as complex and simple as constructing and maintaining data pipelines, tools such as Flink, Kafka, Spark Streaming, etc. are vital for achieving a successful transition.
When it comes to programming and scripting, data engineers, along with having a solid understanding of Python, must also know how to work with specific frameworks such as Pandas, Dask, Pyspark, Scala, etc. In this day and age, knowing how to use SQL is equally important as it enables users to manage structured data in relational and cloud-based databases. In today’s world, emerged languages such as Rust and Go have proven their worth due to increased speed and memory efficiency to handle large scale data workloads.
4. Soft Skills
Skills like communication, collaboration, and problem-solving are now regarded as equally important as technical expertise in data engineering. The indeed report stated that 80% of hiring managers say these skills are equally critical as technical skills when bringing on board data engineers.
Data engineers today are required to be effective communicators and possess soft skills such as adeptness at critical thinking, problem-solving, adaptability, and teamwork. These skills make data engineers invaluable, as it enables them to contribute in unprecedented ways and enhance any team’s technical prowess.
Building world-class Data Engineering teams with technology staffing agencies: Closing the data skills gap
Most companies face difficulty in attracting and retaining experienced data engineers due to a shortage of talent. This is why specialized tech staffing agencies are helpful for businesses. These companies are instrumental in onboarding highly skilled professionals, simplifying the hiring process, and, most importantly, ensuring firms get the right people to enable their data strategies.
So, let’s examine how these agencies are able to shrink the skills gap and build competent and agile data engineering teams.
1. Faster turnaround to access pre-qualified candidates and increased candidate reach
Staffing agencies give companies quick access to a pool of vetted data engineers and thus save manpower and time. With their vast resources of skill databases, they have greater coverage than conventional recruitment methods. They can quickly identify and engage with skilled candidates that meet specific business requirements because of their industry knowledge and recruitment experience.
2. More efficient recruitment processes
Tech staffing companies make recruitment more examples by using candidate networks, technology, and remote offices. Because of this, companies can hire data engineers immediately without the need to go through the traditional hiring process. Those companies can simultaneously solve the hiring problem without the burden of extended hiring systems. Also, their industry hire crazes gives access to non-active candidates, allowing companies to quickly manage their data engineering without any loss of quality or efficiency.
3. Knowledge in new developments
Because of the fast-changing nature of their field, tech staffing companies have the tools to source candidates who specialize in new technologies like AI, big data, and cloud analytics. Their understanding of the industry coupled with constantly working with technology companies gives them a deep pool of top candidates with the latest tools and frameworks.
This professional skill guarantees that the firms can respond to new changes in technology without having to unnecessarily spend time and resources in upskilling or reskilling internal teams. By keeping ahead of technological change, these firms supply companies with specialized data engineers who improve productivity and innovation.
4. Flexible hiring models
Businesses often look for varying degrees of involvement with different levels engagement as dictated by project requirements. IT staffing companies offer flexible hiring models to businesses so that they can manage their data engineering resources relative to project requirements. Whether companies require short-term contracted specialists, contract-to-hire positions for skill assessment, or permanent employees for long-term development, staffing companies meet those needs. Finally, they even have remote or offshore teams through their global talent pool.
This flexibility enables firms to manage their costs effectively and still provide them top-quality talent when necessary and mitigates the loss of opportunity cost of adjusted business needs. IT staffing firms provide agility and innovation to businesses through flexible hiring models which remove the constraints of inflexible business models.
5. Employee retention and workforce stability
Not only do tech staffing agencies assist firms in sourcing talents, but they also develop plans to help with retention and workforce stability. This also entails cultural alignment assessment. Intensive screening and vetting processes ensure that candidates are matched to roles that best fit their skills, career aspirations, and the company culture.
In addition, many staffing firms provide learning and development opportunities, which helps to improve employee satisfaction while managing attrition rates. In addition to these, they provide employee engagement initiatives and compensation which help increase satisfaction, reduce attrition, and motivate staff to help create a stable data engineering team.
Stride Digital, an expert in IT consulting, solutions, and staffing, closes the existing skill gap by providing businesses with qualified data specialists and professionals through team extension, staff augmentation, and targeted recruitment. From joining teams already in place, to establishing offshore development centers, and to running deep technology skills tests, Stride Digital makes sure businesses get the talent needed for data innovation.
With leadership support staffing and contract-to-hire services, Stride offers businesses flexibility and expertise, reducing risk while constructing high performance data engineering teams that accelerate growth.
Final Thoughts
While data is one of the main core components of business value, the data engineering function has evolved from simply building pipelines and data repositories into a wide range of modern AI and automation real-time processing technologies.
Effective data understanding and usage can out a company at the forefront of innovation in this ever-changing digital environment. IT staffing agencies are proactively seeking means to help businesses design scalable and efficient data infrastructure, and with their extensive networks, are directly able to supply the most sought-after data engineers. Struggling to find top data engineering talent? Reach out to Stride Digital and leave your worries to the experts!
