E-mobility, Connectivity and Autonomy are redefining the traditional auto business, thus creating a tremendous disruption in the industry. The demand for embedded systems engineers, the backbone supporting the advancements in these areas is expected to more than double in the next two years. Industry analysts report that the global automotive embedded system market is projected to grow by $3.4 billion by 2024. The market for sensor technology used extensively in passenger safety, infotainment systems & navigations, will grow seven-fold in the same timeframe.
While the data points to a steady rise in demand, the ground reality is that there is a severe talent shortage of embedded systems engineers. The rapid evolution of automotive tech and a lethargic attitude to up/reskilling is to be blamed for this problem.
While in the traditional auto industry, the focus was limited to hardware and physical level innovations such as:
- Improving built-in infotainment systems
- Optimizing vehicle performance
- Advancing safety features on the physical level
The modern automotive industry has shifted gears towards:
- Building fully autonomous & eco-friendly solutions
- Leveraging the connected ecosystem (V2I, V2V, V2X & IoT)
- Customer experience–focused design and features
These modern consumer requirements heavily rely on embedded systems engineers. Although previously considered as a very niche and hard-to-get-into field, this role is now easier to get into thanks to standardization of systems.
The push to connect everything to the cloud has spurred a huge talent shortage in this domain
Today’s embedded software engineers operating using a drastically different skillset from their predecessors. They are no longer restricted to low-level coding and debugging. Instead, they are expected to know how to call APIs and have hardware perform actions based on the returned value. Universities, as usual, are behind the curve in imparting these new skills. The result is a skills mismatch.
Impact on Traditional Job Roles in Automotive
Before we dive deep into how we can solve the Embedded Systems Engineer crisis, let’s take a brief tour to see how other roles are being disrupted as well.
Demand for traditional roles like Safety Engineer and Powertrain Engineer have declined by 14% whereas digital roles like Advanced Driver-Assistance Systems (ADAS) Safety Engineer, Electrical/Hybrid Powertrain Engineer, AR/VR Engineer & Data Analyst have increased by 30%.
Other key digital roles vital for the digital transformation journey for the automotive industry are:
- Machine learning specialist
- Computer vision engineer
- Big Data Developer/Engineer
- ADAS Algorithm Data Scientist
- Connected vehicle Telematics Engineer and other new-age roles
The Battle for New-Age Talent
It’s not just the automotive industry. Digitization needs across every other industry have created an intense hiring battle for digital roles making talent acquisition highly challenging.
While the digital talent growth for the auto industry stood at 20% as of late-2019, the numbers were 25% for retail, 22% for insurance and 29% for enterprise software sectors.
With a combined annual demand of 70,000 – 80,000, job opening in the US for IoT, AI/ML, Big data & Analytics, RPA & Web development are always short on talent. Even in the general digital talent market, the gap is expected to double to ~3 MM by 2024.
Reskilling becomes a key option for HR and business leaders as companies address the dual challenges of hiring competition and lack of career growth opportunities for the existing workforce.
In the below image, we have analyzed how a traditional workflow for an Embedded Software Engineer would evolve to a digital workflow.
For example, the demand for Embedded C and system development on the Linux platform has transformed into developing automation tools in C++/Matlab/Python.
Reskilling for a Digital Role – Embedded Software Engineer
With Reskilling, employees working in job roles facing disruption have the option to shift to an adjacent, sustainable position that will help them in their long-term career.
We present a roadmap for an Embedded Software Engineer to transform into a digital role of ADAS Data Scientist with an intermediary role of ADAS Software Engineer.
Going through the industry requirements for this role, we have narrowed down the set of required skills to:
- Hadoop
- R Programming
- Spark
- Big Data
- Scala
- Knowledge of data visualization tools
By taking up the course of Self-Driving Car Engineer offered by Udacity, a person can transition to the intermediary role of ADAS Software Engineer. From here, the course on Introduction to R for Data Science from FutureLearn or similar courses from other vendors will equip a person to successfully complete the transition to ADAS Algorithm Data Scientist. We estimate this complete transition to take about 6-9 months.
We arrived at this roadmap using Draup’s proprietary talent module to analyze multiple career paths on the Reskilling Navigator tool.
Draup helps HR leaders understand the digital career paths of their traditional workforce and reskill them with micro and macro learning modules. By analyzing existing & emerging roles opening in new job families, Draup for Talent can predict optimized future career paths and courses/certifications to fast track the transition.
