How to Hire and Retain Data Warehouse Developers

| March 27, 2024
data warehouse developers

The projected data warehouse developer job growth rate is 21% from 2018-2028, with about 284,100 new jobs for data warehouse developers projected over the next decade, according to Zippia. This surge in demand for data warehouse talent is being felt across businesses and institutions, highlighting the critical role these developers play in managing the vast volumes of data generated today. 

data warehouse developer jobs over time
Image source: https://www.zippia.com/data-warehouse-developer-jobs/trends/

Recognizing this, organizations are actively seeking strategies on how to find and keep data warehouse talent, underscoring the countless opportunities for growth, innovation, and increased efficiency that data warehousing presents. However, the challenge of hiring data warehouse developers is substantial for many organizations. The lack of the right talent in data warehousing can derail an organization’s data strategy and substantially impact its success.

This article discusses the challenges of hiring and keeping data warehouse developers and suggests ways to address these issues.

Understanding the Job of a Data Warehouse Developer

A Data Warehouse Developer is a specialized IT professional who plays a crucial role in creating and maintaining complex data storage systems for business intelligence. They design, build, and optimize data warehouse architecture using tools like SQL databases, ELT (Extract, Load, Transform) processes, and data modeling techniques. Their role includes transforming raw data into structured formats for strategic decision-making, requiring technical expertise, analytical skills, and business process understanding.

What does a Data Warehouse Developer do?

Data Warehouse Developers crucially bridge the gap between an organization’s technical capabilities and business needs. They must collaborate closely with Business Developers, Managers, and Analysts to receive accurate requirements and align everyone’s understanding of the Data Warehouse’s purpose. Through collaboration, they gather comprehensive input on the required deliverables, reports, and analyses, ensuring that Data Warehouse solutions are precisely tailored to meet specific business objectives and priorities.

By actively engaging with stakeholders across different departments, Data Warehouse Developers can better comprehend the intricacies of various business processes and challenges. This collaboration fosters a shared vision and facilitates the development of Data Warehouse solutions that are not only technically sound but also highly relevant and valuable to the organization. Ultimately, this synergy between Data Warehouse Developers and business stakeholders leads to more effective decision-making, improved operational efficiency, and better utilization of data-driven insights.

Key Responsibilities of a Data Warehouse Developer

Data Warehouse Developers

On a day-to-day basis, the Data Warehouse Developer delivers data and information related to Business Intelligence BI to their organization to help them make data-driven decisions. They have experience in BI development, implementations, data architecture, and warehousing. Let’s look at the tasks and responsibilities of a Data Warehouse Developer:

  • Designing and implementing robust data warehouse architectures. 
  • Creating and developing ETL (Extract, Transform, Load) processes to integrate data from multiple sources. 
  • Understanding the organization’s specific needs for analytics and creating data models that accurately address those metrics.
  • Work with Analysts to confirm the key requirements for the Data Warehouse to ensure the proper deliverables and reports are being generated.
  • Ensuring the security of the data warehouse and compliance with data governance standards.
  • Prepare various code designs and ensure their efficient implementation.
  • Optimizing data warehouse performance through indexing, partitioning, and query tuning.
  • Collaborating with business analysts and data scientists to deliver appropriate data structures.
  • Writing complex SQL queries. 
  • Testing and troubleshooting data systems. 
  • Documenting the data warehouse environment and maintaining metadata repositories.
  • Keeping abreast of new technologies and methodologies in data warehousing and big data.
  • Providing support to the software development lifecycle.
  • Monitoring data warehouse work and providing subject matter expertise.

Increasingly, organizations are looking for professionals who can effectively analyze, manage, and interpret their data to make informed decisions and ensure competitive advantage. However, due to a shortage of Data Warehouse developers, companies often find themselves in a fix to meet these growing demands. 

Reasons for Skills Shortages

The skills shortage in data warehousing reflects the challenge of finding competent professionals with the skills to meet the growing demands of organizations. Let’s examine some factors for this shortage: 

  • Rapid Technological Advantages: The speed at which technology and data processing tools are evolving requires professionals to constantly learn and adapt to the latest technologies and skill sets which can be overwhelming for developers. 
  • Complexity of Operations: The complexity requires a data warehouse developer to manage large amounts of data, which demands a high level of technical knowledge and analytical skills. This necessity limits the availability of professionals.
  • Interdisciplinary Requirements: Working with large datasets and data warehouses requires qualified experts in a number of disciplines, such as computer science, statistics, mathematics, and business administration. It also encompasses understanding the specific company’s needs when building a Data Warehouse, adding complexity to the hiring process due to the need for expertise in multiple domains.
  • Demanding Working Environment: Data Warehouse Developers often encounter the possibility of additional working hours during critical phases of a project, such as deadlines for data migration or system upgrades. The role is computer-intensive, demanding continuous learning to keep up with evolving data technologies and methodologies, making it both intellectually stimulating and technically challenging.
  • Implementation: Lacking enough skilled developers may significantly delay or outright cancel the implementation of new IT solutions, leading to reduced operational efficiency and revenue loss.
  • Integration: If companies cannot secure enough skilled development staff, they may find themselves struggling to combine new and legacy technologies while simultaneously encouraging the adoption of new solutions among staff. 
  • Innovation: Most IT executives now say that the shortage of skilled talent makes it harder for them to adopt emerging technologies. With customers now expecting consistent, connected experiences, innovation issues can put companies behind the curve.

Why Data Warehouse Developers Are Hard To Find And What Companies Can Do

For the past few years, companies have considered the lack of IT expertise their biggest challenge. Let’s look at some reasons that contribute to the ongoing shortage. 

Supply and Demand

Problem: Growth in demand for developers outpaces supply.

Solution: To help bridge the gap, some companies have established partnerships with local colleges and universities that offer students the chance to learn in real-world environments. This can help businesses connect with the next generation of developers and create an education-to-employment pipeline. 

Time and Effort

Problem: Hiring skilled IT staff requires more time and effort than other roles because the pool of developer candidates is smaller than the volume of applicants for other positions. Additionally, employers must put in effort to ensure that applicants are well-suited for both the role and the company.

Solution: To secure the best data warehouse developers, companies are engaging specialized IT recruitment agencies and using social media platforms like LinkedIn to expand their talent pool and directly engage with prospects. This strategy streamlines the hiring process and focuses on attracting qualified candidates. Additionally, investing in continuous learning and development programs for current staff helps build internal expertise, enhancing retention and fostering loyalty among developers. This combined approach of strategic recruitment and internal talent development addresses the challenges of hiring and retaining developers in a competitive market.

Adapting to Evolving Technologies

Problem: Data Warehouse Developers face challenges in keeping up with evolving technologies and methodologies, leading to potential skill gaps and inefficiencies in implementing modern solutions.

Solution: Companies can enhance their data warehouse developers’ skills and productivity by investing in continuous learning programs, and offering training, workshops, and certifications on the latest in data warehousing and technology trends. Promoting a culture of experimentation and innovation further empowers developers to stay current with industry changes, driving effective data management strategies in a competitive market.

Retention and Churn

Problem: In the wake of the Great Resignation phase that hit organizations after the pandemic, many developers are resigning from their current jobs for greener pastures if they don’t feel appreciated.

Solution: Because of the dearth of data warehouse developers available in the market, retention is critical for organizations. This not only means paying well but also offering additional quality-of-life benefits.

Work-life Balance

Problem: Burnout is a problem for data warehouse developers who are often under intense pressure to deploy, integrate, and manage services. 

Solution: The harder companies push developers to achieve business goals, the more likely they are to miss their targets as developers look for other employers that respect their work-life balance.

So, Is a Data Warehouse Developer a Good Career Path?

Data Warehouse Developers

A career as a Data Warehouse Developer is challenging yet rewarding, ideal for those passionate about building reliable data warehouses, continuous learning, and upholding high data quality standards. This role is in high demand as organizations increasingly rely on data for decision-making, offering a promising career path with high pay, opportunities for advancement to positions like Data Warehouse Architect or Business Intelligence Manager, and the flexibility to work remotely for better work-life balance.

The growing need across industries for data-driven insights ensures job security and opportunities for career growth in data management and analytics. Pursuing a career in this field not only offers financial and professional rewards but also plays a crucial role in enabling organizations to make informed decisions based on data.

The Way Forward for Organizations

Data warehouse developers are still hard to find, and this shortage isn’t going away anytime soon. Hence, companies must consider alternatives to traditional hiring practices.

  • Automation: With the evolution of artificial intelligence (AI) solutions, companies can automate repetitive tasks that are critical but don’t require data warehouse developers to intervene. Automation tools like WhereScape 3D and WhereScape RED can help streamline data warehouse development, significantly cutting project timelines from months to days. This strategy allows businesses to efficiently scale their developer resources, utilizing data warehouse automation over manual labor for greater flexibility.
  • Up-skilling: Companies must consider up-skilling internal employees who have the interest and ability to expand their skill set with customized internal training programs.  
  • Outsourcing:  Businesses may consider outsourcing developer roles to IT service management firms that can provide access to skilled data warehouse developers on demand.

While these solutions can’t fully replicate the function of a skilled data warehouse developer, they can help bridge the gap. 

Seize Your Data Warehouse Career Opportunity

Data Warehouse Developers can expect competitive salaries, growth in career advancement, and learning opportunities to work with cutting-edge technologies. With data warehouse development tools and technologies playing a pivotal role in the digital economy, the career path of a Data Warehouse Developer is both stable and promising, offering long-term growth and the opportunity to specialize in a variety of industries.

Organizations can foster a culture that retains top data warehouse talent by emphasizing human-centric work and developer experience.

Elevate your data warehousing skills with WhereScape. Discover how automation can accelerate your projects and free your team for more innovative tasks. Request a demo with WhereScape today and streamline your data warehouse development or try WhereScape RED out for free here.

Deep Dive into WhereScape RED: Features and Benefits

Transforming a business’s various databases and files into actionable insights and reports is crucial, but incredibly time-consuming with traditional tools. Fortunately, with data warehouse automation tools like WhereScape RED, organizations can take advantage of a...

ETL vs ELT: What are the Differences?

In data management, the debate between ETL and ELT strategies is at the forefront for organizations aiming to refine their approach to handling vast amounts of data. Each method, ETL vs ELT, offers a unique pathway for transferring raw data into a warehouse, where it...

8 Reasons to Make the Switch to ELT Automation

Extraction, loading, and transformation (ELT) processes have been in existence for almost 30 years. It has been a programming skill set mandatory for those responsible for the creation of analytical environments and their maintenance because ELT automation works....

What is a Data Model?

A data model depicts a company's data organization, standardizing the relationships among data elements and their correspondence to real-world entities' properties. It facilitates the organization of data for business processes and information systems, offering tools...

Webinar Recap: Navigating the Future of Data Analytics

In an era where data is the new gold, understanding its trajectory is crucial for any forward-thinking organization. Our recent webinar, "Capitalizing on Data Analytic Predictions by Focusing on Cross-Functional Value of Automation and Modernization," hosted in...

Data Automation Levels

The concept of automation has seamlessly integrated into many aspects of our lives, from self-driving cars to sophisticated software systems. Recently, Mercedes-Benz announced their achievement in reaching Level 3 in automated driving technology, which got me thinking...

Related Content

Deep Dive into WhereScape RED: Features and Benefits

Deep Dive into WhereScape RED: Features and Benefits

Transforming a business’s various databases and files into actionable insights and reports is crucial, but incredibly time-consuming with traditional tools. Fortunately, with data warehouse automation tools like WhereScape RED, organizations can take advantage of a...

ETL vs ELT: What are the Differences?

ETL vs ELT: What are the Differences?

In data management, the debate between ETL and ELT strategies is at the forefront for organizations aiming to refine their approach to handling vast amounts of data. Each method, ETL vs ELT, offers a unique pathway for transferring raw data into a warehouse, where it...

Deep Dive into WhereScape RED: Features and Benefits

Deep Dive into WhereScape RED: Features and Benefits

Transforming a business’s various databases and files into actionable insights and reports is crucial, but incredibly time-consuming with traditional tools. Fortunately, with data warehouse automation tools like WhereScape RED, organizations can take advantage of a...

ETL vs ELT: What are the Differences?

ETL vs ELT: What are the Differences?

In data management, the debate between ETL and ELT strategies is at the forefront for organizations aiming to refine their approach to handling vast amounts of data. Each method, ETL vs ELT, offers a unique pathway for transferring raw data into a warehouse, where it...