One Simple Chart: Data Engineering jobs in the U.S.

It’s been a few months since I looked at data on job postings. In my most recent post in Dec/2020 I focused on reinforcement learning (RL), which in terms of number of job postings, barely grew on a year-over-year basis. The good news is that it appears that employers are once again starting to post more1 job openings. As the chart below shows, RL job postings have grown over 30% year-over-year, as did job postings that contained the phrases “machine learning” (up 26.4%) and “data analytics” (up 32.9%).

But the fastest growing term (at least among the ones I track closely) is “data engineer”, which grew 35.1% year-over-year. A closer examination of April/2021 job descriptions surfaced the following terms that appear frequently in data engineering job postings:

  • big data
  • data pipelines
  • data warehouse
  • data quality
  • data architect/architecture
  • data management
  • cloud
  • data warehouse architecture
Job postings in key U.S. Technology hubs

It’s heartening to see data quality among the tasks being prioritized by those currently hiring data engineers. In a recent post on data cascades, I highlighted findings from an important new study from Google Research. Organizations serious about AI really need to increase their emphasis on tools and processes that ensure data quality from the point of collection to machine learning model deployment and inference.

What about reinforcement learning job postings? Here are some common terms that appeared in RL job descriptions in April 2021:

  • machine learning
  • deep learning
  • artificial intelligence
  • research scientist
  • data scientist
  • computer vision
  • natural language
  • machine learning engineer

The final observation is that TensorFlow remains more popular than PyTorch – at least among companies who are hiring in the U.S. metro areas listed on the chart. Furthermore the number of TensorFlow job postings grew faster year-over-year compared to PyTorch.

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[1] Unlike the numbers from my previous post in Dec/2020, the numbers on this post are based on a very simple de-duplication process (using company name and job title).

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