Trends and hype cycles are common in the tech industry, with new technologies emerging every year sparking discussions about their potential impact. Here are some of my observations from recruiting in this space, corroborated with insights from sources such as LinkedIn, Stack Overflow, GitHub etc.

What are the most popular programming languages and how does it relate to salary? Looking at TIOBE’s Index, I’m not too surprised to see Python right at the top of the list given how AI’s really taken off in public parlance and how prevalent the language is in that use case. But what’s this at No. 2? Surprisingly enough, we find C occupy the runner-up spot and this is also the case in Stack Overflow’s survey. This is likely a reflection of the growth of IoT devices although this hasn’t quite translated into a spike in demand among our hiring managers (yet). Additionally, Java and C# continue to maintain their popularity, and we’re noticing an increasing number of job postings for Go and Rust roles.

If we consider the popularity of a language as reflecting the presence of a larger pool of developers in the job market, it is reasonable to expect that salaries for popular languages would decrease, while those for less popular languages would increase. In the survey, popular languages like JavaScript, HTML/CSS, and Python have seen a contraction in median salary, ranging from 5% to 10%. In contrast, less popular languages such as APL, Crystal, and SAS have witnessed impressive double-digit growth. There could be a point to be made in having a “very particular set of skills”.

Developers working with “admired” languages like Rust, Elixir, and Zig reported salaries that are 20% or more higher than the overall median developers — this “admired” tag being defined as languages that developers indicate they would like to continue using having tried it out in the past year. While admiration is useful in separating hype from reality, there is no direct correlation between admiration and financial security. Languages like Python, TypeScript, and HTML/CSS, despite having high admiration scores, only marginally outperform the overall median salary.

When it comes to data, more organizations are embracing modern data stacks, often leveraging cloud data platforms offered by AWS, Microsoft Azure, Google Cloud, Databricks, and Snowflake. While data professionals have traditionally had a multitude of low and no-code tools at their disposal, there is a growing conversation around Python and Rust potentially becoming the standard languages in data engineering. Notably, transformation tools like dbt are gaining considerable traction, and being familiar with them can be advantageous. Despite this, the scarcity of professionals experienced in “legacy” technologies presents some well-compensated job opportunities.

At the end of the day, the popularity of a technology or programming language does not guarantee significant salary growth. Instead, valuable opportunities can arise from finding a niche to specialize in. Thriving in the dynamic field of technology requires a proactive approach to continuously acquiring new skills, obtaining certifications, seeking mentorship, and addressing weaknesses to become a better-rounded tech professional.