Layoffs.fyi estimates that tech companies laid off over 260,000 employees in 2023. And in the first five months of 2024, nearly 85,000 workers were laid off. But the effects of this shift in the tech labor market haven’t been felt evenly across all technical disciplines. A select few roles have proven highly resilient despite the tech industry headwinds.

Let’s see which jobs continue to thrive and why they are crucial in the ever-changing tech industry.

Understanding Resilience in Tech Roles

Resilient roles continue to be in high demand despite fluctuations in the job market. These roles adapt to changes, maintain their importance, and often see increased demand. As we’ll see, data engineering is an example of a highly resilient discipline, with demand for data engineering roles rising by 102% from their 2022 highs.

On the flip side, roles that are not resilient can struggle to maintain their demand, often seeing dips in hiring or even mass layoffs. This decline can be attributed to a range of factors, including automation, AI advancements, and changes in business needs. 

For example, demand for mobile engineers has fallen 23% due to AI frameworks (like TensorFlow and PyTorch) simplifying tasks like image recognition, natural language processing, and recommendation systems.

Methodology

Our data comes from our 2024 Developer Skills Report, which combnies survey responses from developers, employers, and recruiters with data from the HackerRank platform.

Our list defines resilience by ranking the roles that demonstrated a consistent or increasing volume of coding test invites between 2022 and 2023.

The 5 Most Resilient Tech Roles

 1. Data Engineer

Data engineers are pivotal members of the data pipeline. They focus primarily on the architecture and optimization of data platforms. Their responsibilities encompass building systems for data ingestion, storage, analysis, visualization, and activation of vast datasets.

Job Responsibilities:

• Designing and developing scalable data pipelines
• Ensuring data quality and consistency
• Collaborating with data scientists to understand data needs
• Implementing data security measures

Why the role is important:

Data Engineers are essential because they create the backbone for data operations. With businesses increasingly relying on data-driven insights for decision-making, robust data infrastructure is paramount. The growing ubiquity of AI has also bolstered the demand for this skill set, with data engineers proving vital to the sourcing of data for data-hungry AI models.

As such, the demand for data engineering roles has been resilient, with a notable increase in monthly invites by 102% from their 2022 highs. 

 2. Data Analyst

Data analysts interpret data and provide actionable insights. They are crucial in translating raw data into meaningful information to drive strategic decisions.

Job Responsibilities:

• Analyzing complex datasets to identify trends and patterns
• Creating visualizations to present data insights
• Conducting statistical analysis
• Collaborating with business units to understand their data needs

Why the role is important:

In an era when data is considered the new oil, data analysts refine this resource. Their ability to derive insights from data helps businesses optimize operations, improve customer experiences, and drive innovation, making their role indispensable in any data-centric organization.

 3. Cloud Security & Cybersecurity Engineer

Cloud security and cybersecurity engineers defend organizations against a wide range of digital threats, including data breaches, malware and ransomware attacks, and phishing attempts. They protect sensitive information, prevent operational disruptions, and combat fraudulent activities. This protects sensitive user and corporate data while ensuring the company’s reputation and financial stability.

Job Responsibilities:

• Designing and implementing security measures
• Monitoring networks for security breaches
• Conducting vulnerability assessments
• Ensuring compliance with security standards

Why the role is important:

Put simply, security skills are indispensable. Cybersecurity maintains customer trust, ensures regulation compliance, and preserves operational continuity. By safeguarding data, companies foster customer loyalty and avoid legal penalties while also preventing revenue loss and maintaining productivity.

Organizations avoid costly recovery efforts and regulatory fines by averting data breaches and reducing downtime. Additionally, robust cybersecurity measures diminish the risk of ransomware attacks, eliminating the need for expensive ransom payments and subsequent recovery expenses.

Because of the many essential benefits they provide to both companies and consumers, cybersecurity roles are highly resilient.

 4. Site Reliability Engineer

Site reliability engineers (SREs) are responsible for maintaining the reliability and performance of IT systems. They bridge the gap between development and operations by applying a software engineering approach to IT.

Job Responsibilities:

• Monitoring system performance and reliability
• Automating operational tasks
• Managing incident responses
• Ensuring system scalability and efficiency

Why the role is important:

SREs are critical in ensuring that digital services are always available and high performing. Their work is essential in minimizing downtime and ensuring users have a seamless experience. The resilience of this role stems from the constant need to keep systems running smoothly, regardless of market conditions.

 5. Machine Learning Engineer

Machine learning engineers design, build, and deploy machine learning models. They work closely with data scientists to develop algorithms to learn and make data predictions.

Job Responsibilities:

• Designing machine learning algorithms
• Implementing machine learning models into production
• Evaluating model performance
• Collaborating with software engineers to integrate models

Why the role is important:

Machine learning is at the forefront of the most exciting technological innovations, driving advancements in artificial intelligence, predictive analytics, and automation. Machine Learning Engineers are essential for harnessing the power of data to create intelligent systems. The growing adoption of and reliance on AI-driven solutions underscores the importance of – and opportunity for – this role.