The number of tech jobs around the country has been steadily increasing for most of 2021, with the total number of job postings surpassing 365,000 in May. We haven’t seen those kinds of numbers since September 2019. And it’s not just in the traditional tech hubs like New York and San Francisco. We’re seeing impressive numbers in places like Austin, Milwaukee, and Raleigh.
At Averity, we’re seeing an increase across the board from tech companies in search of top-level talent. There are tons of companies out there looking for Back-End Engineers, and barely enough job-seekers to keep up with demand. The three most popular roles that companies are hiring for are Python Engineers, Golang Engineers, and Node.JS Engineers. There are more Python Engineers than Go and Node Engineers combined, but the demand still greatly outweighs the supply of talented Back-End Engineers.
Below are some of the other areas of expertise where there’s a tremendous amount of growth:
Data Scientists, Machine Learning Engineers, and Data Engineers. Companies know the value of data. Moving forward, companies that exploit every potential facet of their data will come out on top. By extracting the true meaning of data, Data Scientists help companies maximize their performance. Data Scientists need to have a combination of excellent technical skills, business acumen, and effective communication skills to ensure they can convey their findings to non-technical stakeholders. The skills employers are looking for most include knowledge of Python and its accompanying ML packages and the ability to apply machine learning models using a variety of techniques. They want a minimum of a master’s degree in a quantitative or STEM field, experience with deep learning, and knowledge of such tools as Tensorflow, Keras, and PyTorch.
Data Engineers create an organization's overall data infrastructure, with the primary function of building data pipelines and data warehouses. They collect the data, clean it, validate it, and prepare it in a format all other stakeholders can easily use. You probably know the term ETL — Extract, Transform, Load — and this accurately describes what Data Engineersdo with the data. The skills employers are looking for most in Data Engineers include familiarity with multiple languages used to build data pipelines (Java, Scala, Python), multi-cloud experience (AWS, GCP) and knowledge of building data warehouses (RedShift, Snowflake, BigQuery). A degree in computer science is very desirable, and experience with big data and tools such as Spark can set you apart from the crowd.
A bridge between Data Scientists and Data Engineers, Machine Learning Engineers have skillsets that overlap with each. They take the data from the pipelines created by Data Engineers and feed it into the models built by Data Scientists. Their goal is to create automation between the extraction and implementation to improve scalability. The skills employers are looking for most include fundamental software engineering skills (especially in data engineering), knowledge of languages like Python, experience with big data processing tools like Spark, and familiarity with cloud platforms like AWS and GCP.
DevOps. DevOps is a mindset and a culture that was adapted to speed software to a production environment. The hottest technologies in DevOps are microservices like Kubernetes. Service mesh tools like Istio, which help you map and understand the health of your containers, are also more and more in demand. Lastly, IaC tools such as Terraform are critical because they can tie in all your infrastructure and are cloud agnostic. That’s important as more and more companies run hybrid cloud models.
SRE. Traditional SRE — site reliability engineering — diverges a bit from DevOps. A lot of the technologies remain the same, but the purpose of SRE is reliability, scalability, and observability. The ability to code is becoming integral in SRE roles. Go and Python are what we are seeing at the top of the food chain. Other technologies that come into play are monitoring tools like Helm that help you define, upgrade, and install your K8s clusters. Solutions engineering is becoming a bigger part of SRE because it's less about owning the infrastructure and more about uptime, maintenance, and upgrades to ensure everything is running smoothly.
DevSecOps. There’s a reason why spending on global cybersecurity is expected to skyrocket to more than $60 billion in 2021. Since vulnerabilities can pop up in a system at any time, DevSecOps is a way for DevOps teams to have a security liaison who understands systems, how they talk to each other, and the threat surface that exists. The three top skills companies look for include experience securing a cloud presence, an ability to run and scan for vulnerabilities after each deployment, and experience securing microservices using tools like Twistlock.
Cloud computing.According to a recent survey, companies are allocating close to a third of their tech budget to cloud computing. As more and more companies adopt a “cloud-first” strategy where they analyze which workloads they should move online, they need cloud computing experts to advise them whether it makes more sense to use a public cloud, private cloud, or a hybrid that combines them both. They also work on cloud-native applications, meaning they are developed and run completely in the cloud.
P.S. Want to keep the conversation going? Connect with me on LinkedIn and follow me on Twitter! You can also find Averity on LinkedIn, Instagram and Twitter. Give us a follow to keep up with the latest company news and insights!