The world generates massive amounts of information every day: social media, e-commerce, mobile apps, IoT sensors and digital transactions produce data at all times. However, data on its own has no value if it isn't analyzed and interpreted. That's where data professionals come into play, one of the most in-demand fields in 2026. In this article we show you which are the most sought-after digital data careers, what each profile does and how you can train to take advantage of these opportunities.

Why are data careers so in demand?

The data explosion forces companies to invest in specialized profiles capable of translating information into actionable knowledge. From improving marketing campaigns to detecting financial fraud or predicting product demand, data is the new engine of decisions. This boom explains why data careers keep growing, both in LATAM and in the rest of the world.

Most in-demand digital data careers in 2026

• Data Analyst: interprets data, builds dashboards and creates reports to guide decisions. Key tools: Excel, SQL, Power BI.

• Data Scientist: uses statistics, machine learning and artificial intelligence to solve complex problems and create predictive models.

• Data Engineer: designs and maintains the data infrastructure, pipelines and systems that let you work with large volumes of information.

• BI Specialist: a Business Intelligence specialist, transforms data into business reports for executives and area leaders.

• Machine Learning Engineer: implements predictive models in production environments for digital products and platforms.

Job projection and salaries

According to Glassdoor and Indeed, data roles are among the most in-demand globally. In LATAM, a Data Analyst earns between USD 15,000 and 25,000 a year, while a Data Scientist can exceed USD 30,000 a year depending on experience. In the U.S., the salaries of Data Scientist and Machine Learning Engineer exceed USD 120,000 a year, which makes these professions some of the best paid in the digital world.

How to train in data careers

The advantage of the sector is that you can start from scratch and advance step by step. Coderhouse offers a complete path to train in data:

• Data Analytics Career — comprehensive training in data analytics, SQL and visualization with dashboards.

• Data Scientist Career — complete training in machine learning, applied statistics and programming.

• Data Analytics Course — beginner level, to learn to analyze and interpret data.

• Excel Course — essential foundation for analysis and reporting.

• SQL Course — advanced queries in relational databases.

• Power BI Course — creating dashboards and interactive reports.

• Data Science Fundamentals Course — intermediate level, applied statistics and programming notions.

• Data Diploma — a global view of data analytics, data science and machine learning, ideal for making a professional leap.

If you'd like to keep exploring this topic, you can also read how to build an AI project portfolio to land a job.

Recommended Coderhouse courses

If you want to go deeper into data analysis and applied artificial intelligence, Coderhouse has programs for all levels:

• Data Analytics Course: to learn to analyze data, build dashboards and make decisions based on real information.

• AI Engineering Course: to incorporate AI and machine learning models into your data projects.

• Introduction to Artificial Intelligence Course: to understand the AI ecosystem and complement your data profile with knowledge about language models.

Frequently asked questions

What's the difference between Data Analytics and Data Science?

Data Analytics focuses on analyzing existing data and generating reports; Data Science goes further, creating predictive models and applying machine learning.

Do I need to know math to work in data?

You don't need to be an expert, but you do need to have foundations in statistics and logic. The tools and courses help you develop these skills.

What's the most important tool to start with?

Excel is still fundamental. Then you can add SQL and Power BI, which are the most used in junior positions.

Can you work in data without previous experience?

Yes. Many professionals start with personal projects and introductory courses that let them put together an initial portfolio.

How much does a data analyst earn in LATAM?

On average, between USD 15,000 and 25,000 a year, depending on the country, the company and the professional's experience.

Conclusion

Digital data careers are at the heart of digital transformation. The high demand and competitive salaries make them one of the best professional bets for the future. If you're interested in getting started in this field, the ideal thing is to choose the training path that best suits your profile.

You can start with the Data Analytics Course or the Excel Course, and then advance toward the Data Analytics Career, the Data Scientist Career or even the Data Diploma to make a complete professional leap.

Sources and references

• Glassdoor – Data jobs salaries

• Indeed – Data job postings

• Statista – Data growth reports

• LinkedIn Jobs Report 2024