Industry Benchmarks for Embedded Systems Skills

Struggling to find skilled embedded systems professionals in Australia? You're not alone. The tech industry faces a growing talent gap, especially in IoT, AI integration, and hardware-software expertise. Here's what you need to know:

Key Takeaways:

• Core Skills: C, C++, Rust, and Python programming, microcontroller knowledge (e.g., ARM Cortex-M), and RTOS expertise (e.g., Zephyr, FreeRTOS).
• Emerging Trends: AI integration, RISC-V architecture, IoT protocols like MQTT, and security-first practices (e.g., Rust adoption).
• Testing & Tools: Use of Unity, VectorCAST, and Jenkins for validation and CI/CD workflows.
• Certifications: ISO 26262 (automotive), DO-178C (aerospace), and TÜV Functional Safety Engineer Certification.
• Skill Gaps: 65% of companies report difficulty filling embedded software roles, with a projected semiconductor workforce shortage of 1.5 million by 2030.

Why it matters: Embedded systems power Australia's automotive, healthcare, and industrial sectors. Staying ahead means mastering technical skills, aligning with industry standards, and embracing continuous learning.

Quick Comparison:

Start building your expertise today. Whether you're an engineer or an organisation, aligning with these benchmarks ensures you're prepared for the future of embedded systems.

Mastering Embedded Systems: Essential Skills and Trends

Core Technical Skills Required

Building a career in embedded systems relies on mastering a blend of hardware and software expertise. These technical skills are the tools engineers use to design, implement, and troubleshoot systems that power everything from automotive ECUs to industrial automation across Australia's tech industry. A solid grasp of these fundamentals is crucial for tackling more complex challenges in integration and security.

Programming Languages and Development Tools

In embedded systems, programming languages are the foundation of development. Engineers need to be proficient in multiple languages tailored for resource-constrained environments.

• C: The backbone of embedded programming, used in over 60% of projects worldwide. Its low-level control and efficiency make it indispensable.
• C++: Essential for complex applications, especially in the automotive sector, where nearly 40% of embedded software relies on it. Its object-oriented features enhance scalability and maintainability without compromising performance.
• Rust: Gaining traction in safety-critical applications due to its memory safety guarantees. It's ideal for projects where system failures could have severe consequences.
• Python: Although less common (used in about 5% of embedded code), Python is valuable for IoT and AI applications, thanks to its rapid prototyping capabilities and extensive libraries.

The shift towards memory-safe languages like Rust and modern C++ highlights the industry's focus on security and maintainability. Engineers should match each language to the specific needs of their projects while maintaining strong coding skills and an understanding of hardware design.

Hardware and System Architecture

Beyond programming, understanding hardware architecture is vital. It forms the structural blueprint that allows an embedded system to perform its tasks effectively.

• Microcontrollers vs. Microprocessors:
  Microcontrollers (MCUs) are compact, integrating CPU, memory, and I/O on a single chip, making them perfect for cost-sensitive and low-power applications. Microprocessors (MPUs), on the other hand, focus on high performance and complex computations, requiring external components. Here's a quick comparison:

• RISC-V Architecture: This open-source instruction set is reshaping the industry. By 2025, over 20 billion RISC-V cores are expected to be in use globally, capturing about 6% of the CPU core market. Its customisation and cost efficiency make it a compelling option.
• Memory Architecture: Embedded systems rely on both volatile (RAM) and non-volatile (ROM, Flash) memory for program code and data storage. Engineers must also understand power supply and management, especially for battery-powered devices, to ensure efficiency and longevity.

When designing systems, engineers should prioritise data flow, then build processing elements around it. Application code should avoid direct interaction with hardware registers or memory. Modules should have clear responsibilities and interfaces, with all components designed for automated testing.

"Security must be built from the ground up in embedded systems. Relying solely on software protections is no longer enough." – Dr. Sarah Williams, cybersecurity researcher at SecureTech Labs

RTOS and Communication Protocols

To achieve precise control in embedded systems, engineers need expertise in real-time operating systems (RTOS) and communication protocols.

• RTOS: These systems are indispensable for applications with strict timing requirements, such as automotive controls, medical devices, and industrial automation. Zephyr RTOS, an open-source option with an active community, is particularly popular. Modern RTOS solutions now include cloud-ready features, security-first designs, and AI/ML integration. Commercial tools are also evolving, integrating Zephyr RTOS into DevSecOps workflows.
• Communication Protocols: Both wired and wireless protocols are crucial. Wired options like UART, SPI, and I²C offer different advantages, from debugging to high-speed sensor interfaces. Wireless protocols, including BLE, Wi-Fi, and Zigbee, should be chosen based on factors like power consumption, range, and data rate.

The rise of edge AI is transforming embedded systems by reducing latency and improving security. This trend demands that engineers bridge their hardware knowledge with cloud infrastructure, integrating platforms like AWS IoT or Google Cloud IoT.

Advanced Skills in High Demand

As embedded systems continue to evolve, engineers are navigating a landscape where traditional hardware meets cutting-edge digital technologies. The fusion of IoT, artificial intelligence, and cybersecurity is reshaping the skill set required in this field. Engineers with expertise in these advanced areas are not only in demand but are also unlocking opportunities in high-growth sectors. These skills are becoming the key to staying competitive in the embedded systems industry.

IoT Protocols and Cloud Integration

The Internet of Things (IoT) is transforming industries, and with the global IoT market expected to hit US$1.06 trillion by 2025, the demand for engineers proficient in IoT protocols is surging. These protocols are the backbone of IoT systems, balancing massive scalability with efficiency.

• MQTT has become the go-to protocol for over 60% of IoT developers. Its lightweight design makes it ideal for resource-limited environments, like industrial automation and smart agriculture projects across Australia.
• Matter is addressing long-standing compatibility issues in the smart home ecosystem. With 74% cross-platform compatibility, it’s simplifying interoperability between devices.
• For large-scale deployments, LwM2M (Lightweight M2M) is essential for tasks like device management and firmware updates, helping to optimise costs and operational efficiency.
• Protocols like Wi-Fi, Zigbee, and Thread each offer unique trade-offs in bandwidth and power consumption, making them suitable for specific applications.

Beyond protocols, cloud integration is a critical skill. Engineers must know how to implement secure OTA (Over-The-Air) updates, manage device lifecycles, and integrate with cloud platforms. Designing systems that maintain functionality even during connectivity outages is a must-have capability for career progression.

AI and Machine Learning Integration

AI is taking embedded systems to a new level, enabling smarter, more adaptive platforms. With the global AI in embedded systems market projected to reach US$26.2 billion by 2026, engineers who can merge AI with embedded hardware are poised for success.

• Edge AI is a game-changer, allowing data to be processed locally and reducing reliance on the cloud. In automotive applications, embedded AI powers Advanced Driver Assistance Systems (ADAS), enabling real-time analysis of data from cameras, radar, and LiDAR.
• Healthcare is another area where AI is making a difference. For instance, AI-driven insulin pumps that adjust dosages based on real-time glucose monitoring are improving patient outcomes.
• In the manufacturing sector, AI-powered systems predict maintenance needs by analysing equipment performance in real time. This predictive capability is invaluable for reducing downtime and costs, especially in resource-heavy industries like mining.

Engineers must also focus on model optimisation for devices with limited resources. This includes mastering techniques like quantisation, pruning, and hardware acceleration. New system-on-chip (SoC) products with built-in AI features are gaining traction, requiring expertise in neural processing units.

As AI tools become more integrated into development workflows, they’re enhancing productivity rather than replacing human engineers. As Microsoft CEO Satya Nadella puts it:

"AI won't replace programmers, but it will become an essential tool in their arsenal. It's about empowering humans to do more, not do less".

Security Best Practices

With IoT and AI advancements, security has become a cornerstone of embedded systems design. A staggering 74% of cybersecurity professionals report that AI-powered threats are already a significant challenge, making robust security measures non-negotiable.

Key practices include:

• Implementing Firmware Bill of Materials (FBOM), cryptographic signing, TLS 1.2+, AES-256 encryption, and X.509 certificates to secure devices.
• Ensuring secure OTA updates with rollback capabilities and integrity checks to prevent malicious firmware installations.
• Adopting Zero Trust architecture, which continuously authenticates devices and segments them into micro trust zones to minimise risks.

AI security introduces additional complexities. Research shows that 57% of AI-powered APIs are externally accessible, and 89% rely on insecure authentication methods. Engineers must employ adversarial training and restrict access to training datasets and deployed models using tools like role-based controls and multifactor authentication.

George Cora, CEO of Ardexa, highlights the importance of comprehensive security in IoT systems:

"Effective and secure connectivity must be powered by a 'smart' device able to handle security, encryption, authentication, timestamps, caching, proxies, firewalls, connection loss, etc. Devices must be robust and able to operate in the field with limited support".

Regular vulnerability assessments and continuous monitoring through IoT-aware Network Detection and Response (NDR) tools are critical for identifying and mitigating security gaps.

Mastering IoT protocols, AI integration, and rigorous security practices positions engineers as leaders in embedded systems. These skills are not just technical requirements - they’re the foundation for shaping Australia's digital future and driving innovation across industries. Engineers who excel in these areas are setting themselves up for rewarding careers and exciting projects.

Professional and Testing Skills

Technical proficiency is crucial, but it's the combination of collaboration, communication, and thorough testing that truly sets outstanding engineers apart. These professional skills bridge the gap between technical expertise and successful project outcomes. Let’s take a closer look at the testing, version control, and communication practices that make this possible.

Testing and Validation Methods

Testing embedded systems requires unique approaches due to the intricate mix of hardware and software. Barry Boehm's classic distinction highlights the process perfectly:

"Verification: 'Am I building the product right?'
Validation: 'Am I building the right product?'"

The V-Model is a widely used framework that pairs each development stage with corresponding tests, ensuring issues are caught early. Unlike traditional Waterfall models, this approach integrates testing throughout development, offering more adaptability.

Testing methods typically fall into three categories:

• Black-box testing: Focuses on system behaviour without examining the internal code.
• White-box testing: Analyses internal logic and the structure of the code.
• Gray-box testing: Combines elements of both, offering a balanced approach.

A real-world example of rigorous testing comes from a medical device manufacturer during the COVID-19 pandemic. By implementing a comprehensive testing strategy - including unit testing, static code analysis, hardware-in-the-loop (HIL) simulations, and stress testing - they increased ventilator reliability by 45% and nearly eliminated firmware-related failures.

Modern testing tools tailored for embedded environments are indispensable:

To improve testing outcomes, consider adopting shift-left testing and automated regression testing to catch issues early. Hardware-in-the-loop integration can simulate hardware environments effectively. Compliance with regulations such as ISO 26262 (automotive), DO-178C (aerospace), IEC 62304 (medical devices), and IEC 61508 (industrial automation) adds further complexity. This requires meticulous testing, documentation, and traceability throughout the development process.

While testing ensures quality, version control plays a key role in managing collaboration within complex projects.

Version Control and Development Practices

Embedded projects often involve multiple teams working on intricate technical challenges. Disciplined version control ensures smooth progress and reduces errors. Git, for instance, is used by 87% of development teams.

The benefits of effective version control are clear:

• Teams using source management platforms report a 50% drop in deployment failures.
• Branching strategies boost productivity by 47% and reduce merge conflicts by 52%.
• Feature branches can cut integration issues by 40%.

Clear commit messages also save time, reducing code tracing efforts by 50%, while well-documented logs improve debugging speed by 25%.

Continuous Integration (CI) further enhances development workflows by accelerating feedback cycles, halving post-release defects, and increasing deployment frequency. Structured repositories improve communication and transparency across teams, with 75% of software teams reporting better collaboration. Additionally, maintaining thorough documentation alongside version control can cut onboarding time for new engineers by 50%.

To minimise merge conflicts, resolve them quickly, and encourage regular communication among team members. Using conflict resolution tools and merging code daily can increase team productivity by 50%.

Communication and Documentation

Strong communication and documentation skills are essential for bridging the gap between creative design and practical implementation. Employers rank communication as one of the most important qualifications when hiring engineering graduates. In embedded systems, where hardware and software teams must work closely together, these skills are especially critical.

Maintaining a centralised repository for design specifications, requirements, and interface definitions can save time and prevent costly misunderstandings. Poor documentation is a major contributor to product delays and recalls, with over 40% of software-related recalls linked to inadequate documentation practices.

Test documentation is particularly important for embedded systems. Engineers need clear written and verbal communication skills to create test plans, report progress, and make informed recommendations. Comprehensive documentation also simplifies onboarding and ensures smooth knowledge transfer throughout the project lifecycle.

In Agile environments, where collaboration is key, engineers must communicate complex technical ideas in ways that are accessible to diverse stakeholders. Feedback loops from hardware testing can inform software improvements, creating a cycle of continuous refinement that relies heavily on effective communication.

Beyond technical expertise, soft skills like teamwork, leadership, and a commitment to continuous learning are becoming just as important. These professional and testing skills not only enhance project outcomes but also position engineers as indispensable contributors to their teams, capable of delivering robust, well-documented solutions in a competitive industry landscape.

How Skills Are Benchmarked and Assessed

Evaluating embedded systems skills involves a mix of formal certifications, hands-on assessments, and practical projects. The industry uses comprehensive frameworks to measure everything from basic programming knowledge to advanced system integration capabilities. By combining recognised certifications with real-world challenges, professionals can showcase their expertise in embedded systems.

Industry Skill Frameworks and Certifications

Professional certifications act as trusted indicators of expertise in various areas of embedded systems development. They not only give employers confidence in a candidate’s abilities but also help professionals demonstrate their competence in specific domains. These certifications align with industry trends, ensuring that skills remain relevant to evolving demands.

In safety-critical industries, certifications are indispensable for meeting regulatory standards. For instance:

• Automotive electronic control units (ECUs) certified to ISO 26262 ensure functional safety in vehicles.
• Airborne systems with DO-178C certification comply with aviation safety requirements.
• Medical devices certified to IEC 62304 guarantee software safety in life-critical applications.
• Railway systems certified to EN 50128 meet stringent safety standards.

Here are some key certifications tailored to specific roles:

Brent Eads, Senior Solutions Director at HCL Technologies, explains the role of certifications:

"Certs are not degrees nor particularly good trainings but were intended to confirm experience at a particular set of tasks."

Choosing the right certification depends on career goals and areas of focus. Professionals should aim for credentials that provide hands-on experience with technologies such as IoT, automotive systems, or medical devices. Interestingly, the embedded systems field often leans towards candidates with electrical engineering backgrounds over computer science degrees, due to the critical emphasis on hardware knowledge.

Practical Projects and Scenario Testing

While certifications validate theoretical knowledge, practical assessments reveal how well candidates can apply their skills. These hands-on tests evaluate problem-solving abilities, technical expertise, and the capacity to perform under realistic conditions, complementing the certification process.

"Embedded engineering is a field where technical expertise and problem-solving skills go hand in hand. The ability to identify, analyse, and solve complex problems is critical for engineers working on firmware development, hardware design, and system integration."

A 2025 case study highlights this approach. Candidates for an Embedded Firmware Engineer role were tasked with diagnosing and fixing a malfunctioning sensor interface in 90 minutes. The challenge involved an off-by-one error in the I²C address configuration and a timing issue causing incorrect data reads. Candidates were provided with a development board, sensor module, and sample firmware. While strong candidates verified I²C settings using datasheets, top performers identified timing issues with a logic analyser and adjusted delay loops accordingly. This exercise effectively separated candidates with strong debugging skills from those with limited hands-on experience.

Practical assessments often include:

• Coding challenges to test programming skills in embedded contexts.
• Hardware-in-the-loop (HIL) tests to evaluate system integration capabilities.
• Take-home assignments for tackling complex problems without time constraints.
• Scenario-based discussions to assess problem-solving strategies.

The best assessments are tailored to the role, with tasks that match the candidate's experience level. Clear instructions and realistic timeframes ensure fairness while focusing on evaluating thought processes instead of requiring fully implemented solutions.

Talentblocks builds on industry benchmarks and practical tests to refine skill validation through its platform. It goes beyond traditional certifications to provide detailed skill ratings, offering insights into a professional’s abilities across various dimensions of embedded systems.

The platform’s validation process includes technical assessments and practical demonstrations that measure proficiency in areas like C/C++ programming, hardware interfacing, firmware development, testing, debugging, and real-time operating systems (RTOS). Specific skills assessed include bitmasking, array manipulation, watchdog timers, interrupts, RTOS tasks, and I²C protocols.

Talentblocks also ensures transparency in its assessments, clearly outlining how skills are measured. It offers tailored recommendations to match professionals with opportunities that align with their unique skill sets and experience.

The dynamic nature of the embedded systems field underscores the importance of such validation. According to the US Bureau of Labour Statistics, architecture and engineering occupations - including embedded systems engineers - are projected to grow faster than average between 2023 and 2033, with approximately 195,000 new job openings annually. Regional data shows strong growth rates, such as 23.0% in San Diego and 26.6% nationally from 2020 to 2024.

As one Reddit user, Thermr30, aptly puts it:

"The certificate is being able to talk well during an interview and having the technical knowledge to convince them you are capable of learning the things you don't already know."

This perspective highlights how Talentblocks’ approach addresses both technical skills and communication abilities, recognising that success in embedded systems requires not only knowledge but also the ability to apply and articulate it effectively in team settings.

Conclusion: Matching Skills with Industry Standards

As discussed earlier, aligning technical and professional skills with industry standards is no longer optional - it's a necessity. The embedded systems market is projected to hit A$116.2 billion by 2025, and success in this field demands professionals and organisations stay ahead of the curve in a rapidly changing technical environment.

Key Takeaways

These insights highlight the importance of strategic skill development and hiring practices.

At the heart of embedded systems expertise lies a strong foundation in core programming languages and Real-Time Operating Systems (RTOS). While traditional languages like C remain vital, the industry is gradually embracing modern options. For instance, C++ accounts for about 25% of new projects, and Rust is climbing in popularity, nearing the top ten. This shift underscores the need to balance well-established skills with emerging technologies.

A deep understanding of microcontroller architectures - such as ARM Cortex-M, AVR, PIC, and STM32 - continues to set skilled professionals apart. Paired with proficiency in RTOS like FreeRTOS, VxWorks, and Zephyr, these skills form a technical foundation that employers consistently prioritise. Zephyr, in particular, is gaining momentum, with strong backing from silicon vendors, demonstrating how quickly industry preferences can evolve.

The rise of IoT protocols and cybersecurity as essential skills reflects the growing focus on securing connected devices. This trend aligns with broader industry priorities, where regulatory compliance and security concerns are shaping development strategies.

Beyond technical expertise, professional skills like testing, version control, and effective communication are becoming increasingly important. The shift toward skills-based hiring is a clear indicator of this trend. By 2024, 81% of employers were using skills-based hiring, up from 73% the previous year. In fact, 94% of employers believe that demonstrated skills are a better predictor of job success than traditional resumes.

The validation of these skills has also evolved. Industry frameworks now combine formal certifications with hands-on assessments to provide a well-rounded evaluation. As Bob11, an Embedded Engineer, puts it:

"The most important skill is a passion for learning new things."

This mindset is critical in a field where continuous learning drives both individual and organisational growth.

Moving Forward: What Professionals and Businesses Should Do

To thrive in this competitive landscape, professionals and organisations need to take deliberate steps to enhance their capabilities.

For professionals, the focus should remain on mastering foundational skills while staying up-to-date with new technologies. Since engineers spend 50–80% of their time debugging, sharpening problem-solving abilities is crucial. Additionally, gaining expertise in areas like generative AI and machine learning integration will prepare professionals for the challenges ahead.

The path to success involves developing a broad skill set. Core programming languages like C and C++ remain essential, but professionals should also build expertise in IoT protocols, cybersecurity, and modern development practices. Continuous learning is key in this fast-paced field.

For businesses, embracing skills-based hiring can lead to significant advantages. Companies report that hires based on demonstrated skills stay 9% longer than traditional hires, and this approach can save organisations between A$7,800 and A$22,500 per hire by reducing mis-hires. Skills-based hiring also expands talent pools by nearly 19 times, offering access to candidates with proven abilities. Platforms like Talentblocks streamline this process by providing detailed skill assessments and transparent validation tailored to technical roles. Notably, 87% of companies using skills-based hiring report improved innovation and problem-solving.

As advancements in AI, IoT, and cybersecurity continue to reshape the industry, success will depend on aligning skills with evolving standards and adapting quickly. With applications spanning automotive, healthcare, IoT, and defence sectors, professionals and organisations that prioritise this alignment will be at the forefront of the embedded systems field.

Skill benchmarking is more than just a buzzword - it's the key to ensuring tomorrow's technology is built by professionals equipped to meet increasingly complex demands.

FAQs

What are the key skills for engineers starting in embedded systems, and how can they stay updated with industry trends?

For engineers stepping into the world of embedded systems, mastering programming languages like C, C++, and Python is a must. Equally important is having a solid understanding of computer architecture, hardware design, and real-time operating systems (RTOS). Expertise in areas like device drivers, firmware, and low-level programming becomes increasingly important as embedded systems continue to incorporate AI, IoT, and cybersecurity features.

To keep pace with the latest developments, it's worth paying attention to technologies like RISC-V, Edge AI, and IoT security. Engaging in industry conferences, enrolling in training programs, and keeping an eye on the Australian market - expected to experience steady growth in the years ahead - can help you stay competitive in this dynamic field.

Which industry certifications, like ISO 26262 and DO-178C, are most valuable for a career in embedded systems, and how do they impact job prospects?

Certifications like ISO 26262 and DO-178C hold a strong reputation in the embedded systems industry, especially within safety-critical sectors such as automotive and aerospace. They showcase your ability to work within strict safety and compliance frameworks - qualities that employers in these fields highly value.

If you're looking to sharpen your career edge, consider pursuing these certifications alongside others like the ARM Professional Certificate or targeted training in embedded systems engineering. These qualifications not only deepen your core understanding but also refine advanced technical skills, giving you a stronger position in the competitive job market.

How is AI shaping the future of embedded systems, and what skills should engineers focus on to stay ahead?

AI is reshaping embedded systems, pushing the boundaries of how devices can think, adapt, and operate more efficiently. The rise of edge AI, IoT integration, and intelligent automation is leading to breakthroughs across sectors like healthcare, automotive, and manufacturing.

For engineers looking to stay competitive, there’s a clear roadmap: build expertise in AI programming languages like Python, dive into AI fundamentals such as machine learning and neural networks, and develop a deep understanding of system architecture to seamlessly integrate AI technologies. Keeping a pulse on industry developments and consistently refining these skills is crucial in this fast-changing landscape.