IoT Developer
Snapshot
IoT developers analyse and gather data for interpreting the pattern and predicting the result. They use artificial intelligence for managing the tasks and autonomous decisions, employing machine learning algorithms to create smarter devices through data sensors. IoT developers create software for connecting objects to systems and devices, or for programming these objects to make them function on their own.
IoT developers are vital in a world increasingly reliant on interconnected devices. Your work involves analyzing data streams, identifying patterns, and using those insights to create intelligent systems. You'll be programming devices to function autonomously, integrating them with larger networks, and leveraging machine learning to enhance their capabilities. This role demands a blend of software development skills and an understanding of data science principles.
- • Developing software to connect physical objects (devices, sensors) to systems and networks.
- • Implementing machine learning algorithms to enable devices to learn and adapt.
- • Analyzing data collected by IoT devices to identify trends and predict outcomes.
Where this occupation is in demand
Reported labour shortages and surpluses, by year. Published for occupation groups, not for individual job titles.
Figures cover Information and communications technology professionals — 75 jobs including this one.
In shortage: Belgium, Bulgaria, Cyprus, Czechia and 9 more.
Longest-running shortage: Czechia, 4 years.
Select a place on the map to see its figures.
About this source›
Source: ELA/EURES labour shortages and surpluses. Readings are published at occupation-group level, and cover Europe. Editions differ in annex layout and country coverage, so a change between years does not always mean the labour market changed. Countries in grey were not reported, which is not the same as being in balance.
What these words mean
The four things this section reports
- Reported demand
- Whether employers report needing people in this job — a judgement published by a national or EU body, not a count.
- Where it is heading
- Which way employment in this job is expected to move over the coming years, from an official projection.
- Openings
- Roughly how many openings arise — from growth and from people leaving the job.
- Typical pay
- What people in this job typically earn where the source publishes it. Blank does not mean unpaid; it means nobody publishes it for that place.
A measure is left out when nobody publishes it for that place, rather than shown as zero.
Which way the market leans for you
- In your favour
- More openings than people looking — employers are competing for candidates.
- Balanced
- Openings and candidates are roughly matched.
- Competitive
- More people looking than openings — expect to compete.
- Mixed evidence
- Sources disagree, or the same occupation group is short in one part and oversupplied in another.
Every source resolves to one of these four, so there is a single vocabulary to learn. What differs is the evidence behind it, which is printed underneath each verdict — a measured ratio of openings to jobseekers, or an assessment published by a national body.
How this job compares with other jobs in the same country
- Strong
- Among the strongest in that country
- Good
- Stronger than most jobs in that country
- Mixed
- About typical for that country
- Weak
- Weaker than most jobs in that country
This is a rank within one country, not a score you can carry across borders — the registers behind two countries count different people, so the same number means different things in each. It is also why a job can be among the strongest in a country and still show as Competitive: it leads the field in a market that is crowded overall.
Where these come from
Every figure is published by a national statistics office, a public employment service or an EU body, and each card names its source and the period it covers. Some places are counted monthly, others assessed once or twice a year, so two places on the same map can be describing different moments — the date is always shown.
None of this predicts one person’s chances. It describes a market.
Reported demand · Typical pay · Where it is heading (United States, Ireland, Australia, Malta, United Kingdom)
| Reported demand | Typical pay | Where it is heading | |
|---|---|---|---|
| United States | Not reported | $135,980 2025-05 | +15.8% 2024–2034 · BLS 2024-2034 |
| Ireland | Shortage reported ELA/EURES 2025 * | — | +32.3% 2023–2035 · Cedefop 2026 * |
| Australia | Assessed as balanced Jobs and Skills Australia 2025 * | — | — |
| Malta | Shortage reported ELA/EURES 2024 * | — | — |
| United Kingdom | Not reported | £55,587 2025-provisional | — |
* Published for occupation groups, not for individual job titles.
U.S. Bureau of Labor Statistics (OEWS)
Source: Office for National Statistics, Annual Survey of Hours and Earnings, Open Government Licence v3.0
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Future Outlook for IoT developer
The outlook for IoT developer reflects a balanced mix of automation exposure and durable, human-led work.
How are these scores calculated?
The Resilience Score (0–100) estimates how structurally protected this occupation is from automation and AI disruption, based on task-level analysis. Higher scores mean more human-judgment-intensive tasks. AI Exposure shows the estimated percentage of task hours that current AI capabilities could affect. These are model-derived structural indicators, not predictions about individual job security.
How could IoT developer change as AI adoption grows?
Several task areas may shift toward AI-assisted workflows, so reskilling becomes more important.
Illustrative scenario based on task automatability — not a forecast. Values are rounded the further ahead you look.
Several task areas may shift toward AI-assisted workflows, so reskilling becomes more important.
Illustrative scenario based on task automatability — not a forecast. Values are rounded the further ahead you look.
Model-based estimate. Use it as a planning signal, not a guarantee.
Compare this to your profile
How AI may change this role
Deterministic, model-based interpretation of current role signals — not a guarantee of replacement.
What still depends on people
- develop ICT workflow
Where AI may become a co-pilot
- analyse big data
- perform dimensionality reduction
- utilise machine learning
Tasks most exposed to automation
- use data processing techniques
Vital Signs & AI Vectors
AI Exposure Vectors
0-100%Exposure to AI-assisted analysis, pattern recognition, and predictive modelling tasks
Exposure to content generation, creative augmentation, and large language model tools
Exposure to physical automation, robotics, and sensor-driven task displacement
Exposure to workflow automation, decision-support software, and process digitisation
Technical Details
NexFuture v3.0 estimates automation exposure natively from ESCO essential-skill groups, weighted by skill mass and calibrated against expert anchors. Scores are probabilistic estimates, not guarantees. See the NexFuture Methodology White Paper for full details.
Measures automation exposure. It does not measure pay, demand, or how many jobs exist near you.
What people in this role usually do
Digital Technology
A typical day as an IoT developer
09 09:00 · Morning design information system
10 10:30 · Mid-morning develop ICT workflow
12 12:00 · Midday utilise machine learning
14 14:00 · Afternoon analyse big data
15 15:30 · Late afternoon perform dimensionality reduction
17 17:00 · Wrap-up use data processing techniques
Task order is illustrative. Individual days vary.
What you need to do this work
The skills, knowledge and tools this role calls for — and the traits and rewards that come with it.
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perform dimensionality reduction
Reduce the number of variables or features for a dataset in machine learning algorithms through methods such as principal component analysis, matrix factorization, autoencoder methods, and others.
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utilise machine learning
Use techniques and algorithms that are able to extract mastery out of data, learn from it and make predictions, to be used for program optimisation, application adaptation, pattern recognition, filtering, search engines and computer vision.
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use data processing techniques
Gather, process and analyse relevant data and information, properly store and update data and represent figures and data using charts and statistical diagrams.
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analyse big data
Collect and evaluate numerical data in large quantities, especially for the purpose of identifying patterns between the data.
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develop ICT workflow
Create repeatable patterns of ICT activity within an organisation which enhances the systematic transformations of products, informational processes and services through their production.
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design information system
Define the architecture, composition, components, modules, interfaces and data for integrated information systems (hardware, software and network), based on system requirements and specifications.
ICT software specifications
The characteristics, use and operations of various software products such as computer programmes and application software.
ICT system programming
The methods and tools required to develop system software, specifications of system architectures and interfacing techniques between network and system modules and components.
Internet of Things
The general principles, categories, requirements, limitations and vulnerabilities of smart connected devices (most of them with intended internet connectivity).
principles of artificial intelligence
The artificial intelligence theories, applied principles, architectures and systems, such as intelligent agents, multi-agent systems, expert systems, rule-based systems, neural networks, ontologies and cognition theories.
ICT architectural frameworks
The set of requirements that describe an information system's architecture.
- algorithms
- computer science
- computer technology
- hardware testing methods
- machine learning
- mechatronics
- task algorithmisation
Path to become an IoT developer
What it typically takes to qualify: education level, where it is a regulated profession, and where to study.
Bachelor's or equivalent level
508 programmes in 21 countries teach the core skills of this job. Plus 161 short courses that build single skills.
A few examples, taught in the language of this page:
Bachelor of Science (Honours) in the Internet of Things
South East Technological University · Ireland
Higher Diploma in the Internet of Things
Atlantic Technological University · Ireland
Ara Institute of Canterbury · New Zealand
Malta
These are 6 of 669.
Sources
- 1. Source: Europass Qualification Dataset Register (European Commission)
- 2. Source: Opintopolku.fi (Finnish National Agency for Education)
- 3. Source: Study with New Zealand (studywithnewzealand.govt.nz), Education New Zealand. Copyright in the material is owned by Education New Zealand (All content (c) Education New Zealand). Listings are provided by the education providers, are for information and promotional purposes only, and are not endorsed by Education New Zealand; each provider is responsible for its own content.
- 4. Source: Malta Qualifications Registry, Malta Further and Higher Education Authority (qualifications.mfhea.gov.mt).
Growth Pathways & Similar Roles
Explore typical career progression paths, adjacent skills, and similar roles to plan your next transition.
Where does IoT developer fit?
Similarity scores based on skill overlap from ESCO data.
For organisations
The data on this page, working for your students, clients and staff.
Frequently asked questions
What kind of programming languages are commonly used by IoT developers?
How important is experience with data analytics and machine learning for this role?
I'm interested in a career change – what skills should I focus on developing to become an IoT developer?
How much does IoT Developer pay in the United States?
Sources: ESCO O*NET ELA/EURES Cedefop BLS Data updated October 3, 2026 About our data