Occupation intelligence

IoT developer

Snapshot

Shape the future of connected devices! As an IoT developer, you’ll be at the forefront of innovation, building the software that powers everything from smart homes to industrial automation.

Summary

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.

Key responsibilities
  • • 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.
39%
Resilience Score · 2026 (Higher is better)
Bachelor's or equivalent level 52% AI exposure
Start Career DNA assessment
Labour market

Where this occupation is in demand

Reported labour shortages and surpluses, by year. Published for occupation groups, not for individual job titles.

Shortage reportedSurplus reportedReported in another yearNot covered by this source

Deeper colour: reported the same way in more consecutive years.

Figures cover Information and communications technology professionals — 75 jobs including this one.

13 of 17 in shortage2025All 30 growing3.7Mopenings to 2035

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.

Explore More

Find your career path and explore the science behind our recommendations.

Guiding others? See NexPath for schools and practices.
Quick fit check

Could IoT developer fit you?

Answer three quick questions. This is not a full assessment — it is a teaser to help you decide whether to compare your profile.

Progress0/3

Do you enjoy tasks that require Analytical Thinking?

Do you enjoy tasks that require Attention to Detail?

Do you enjoy tasks that require Cooperation?

NexFuture™

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.

Play the future

How could IoT developer change as AI adoption grows?

Several task areas may shift toward AI-assisted workflows, so reskilling becomes more important.

Significant task-level transformation is estimated in 12 years (around 2038) under the selected Expected Pace scenario.
~35%
Resilience
Automation Risk
EXP~55%
Human advantage
MOAT~40%

Illustrative scenario based on task automatability — not a forecast. Values are rounded the further ahead you look.

2026
2033
2043
AI Adoption Speed:

How AI may change this role

Deterministic, model-based interpretation of current role signals — not a guarantee of replacement.

Human-owned 39% Human-owned
What still depends on people
  • develop ICT workflow
The Human Edge To stay ahead in this role, focus on ICT software specifications and ICT system programming. These human-centric skills are the hardest for AI to replicate in the next 20 years.
Assist 32% Assist
Where AI may become a co-pilot
  • analyse big data
  • perform dimensionality reduction
  • utilise machine learning
Automate 52% Automate
Tasks most exposed to automation
  • use data processing techniques
Detailed Analysis

Vital Signs & AI Vectors

AI Exposure Vectors

0-100%
AI / Machine Learning 32%

Exposure to AI-assisted analysis, pattern recognition, and predictive modelling tasks

Generative AI 3%

Exposure to content generation, creative augmentation, and large language model tools

Robotic & Physical Automation 0%

Exposure to physical automation, robotics, and sensor-driven task displacement

Cognitive Software 0%

Exposure to workflow automation, decision-support software, and process digitisation

Technical Details
Methodology: NexFuture v3.0 Sources: O*NET® 30.3, ESCO v1.2.1 Updated: Aug 2026

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.

Day in the life

What people in this role usually do

Digital Technology

Day in the life

A typical day as a IoT developer

09
09:00 · Morning
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.
10
10:30 · Mid-morning
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.
12
12:00 · Midday
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.
14
14:00 · Afternoon
analyse big data
Collect and evaluate numerical data in large quantities, especially for the purpose of identifying patterns between the data.
15
15:30 · Late afternoon
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.
17
17:00 · Wrap-up
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.

Task order is illustrative. Individual days vary.

Software & Technologies & Knowledge areas
Software & Technologies
3M Post-it AppABC CompilerABC: the AspectBench Compiler for AspectJAdaAdobe AcrobatAdobe ActionScriptAdobe After EffectsAdobe Creative Cloud softwareAdobe DreamweaverAdobe FlexAdobe IllustratorAdobe InDesignAdobe PhotoshopADO.NETAdvanced business application programming ABAPAirtableAJAXAlgorithmic language ALGOLAllaire ColdFusionAlteryx software
Knowledge areas
  • 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.

Cross-sector skills
  • algorithms
  • computer science
  • computer technology
Essential skills
programming computer systems
  • 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.

  • 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.

managing, gathering and storing digital data
  • 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.

analysing and evaluating information and data
  • analyse big data

    Collect and evaluate numerical data in large quantities, especially for the purpose of identifying patterns between the data.

developing operational policies and procedures
  • 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.

designing ict systems or applications
  • 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.

Skill DNA

Skill DNA

Work personality traits and values that define this role

Key traits you need
Analytical Thinking Attention to Detail Cooperation Persistence Initiative Dependability Integrity Concern for Others Innovation Adaptability/Flexibility Stress Tolerance Independence Achievement/Effort Self-Control Leadership Social Orientation
Key rewards you can expect
Trait data is not available for this role yet.
Career progression

Growth Pathways & Similar Roles

Explore typical career progression paths, adjacent skills, and similar roles to plan your next transition.

Common questions

Frequently asked questions

What kind of programming languages are commonly used by IoT developers?
While the specific languages vary by project, common choices include Python, C/C++, Java, and JavaScript. Familiarity with embedded systems programming is often beneficial.
How important is experience with data analytics and machine learning for this role?
A strong understanding of data analytics and machine learning is increasingly important. IoT devices generate vast amounts of data, and the ability to process and interpret this data to improve device performance and functionality is a key differentiator.
I'm interested in a career change – what skills should I focus on developing to become an IoT developer?
Focus on building a solid foundation in software development, particularly with languages like Python or C++. Supplement this with courses or projects in data analytics, machine learning, and embedded systems. Understanding networking protocols (like MQTT or CoAP) is also valuable.
IoT Developer — is there a shortage in Europe?
Yes. In the 2025 ELA/EURES edition, a shortage was reported in 13 of the 17 European countries that assessed this occupation group: Belgium, Bulgaria, Cyprus, Czechia and 9 more. Czechia has reported one for 4 consecutive years. These assessments are published per occupation group rather than per job title.
IoT Developer — what does it pay in the United States?
$133,080 a year at the median, as of 2025-05. State medians run from $79,380 to $174,410. Source: US Bureau of Labor Statistics. This is a United States figure and not a projection for Europe.