DevOps engineers are now expected to have concurrent proficiency in Amazon Web Services (AWS) and Microsoft Azure, according to the platform, which collects and analyzes some 3,000 job descriptions each day for cloud job roles based in the US. Some 70% of job postings that mention Azure also mention AWS, the report found.
Meanwhile, Google Cloud Platform (GCP) places a distant third in the public cloud battle, according to the report: Job postings that mention GCP are significantly lower, with only 7% of those that mention AWS also mentioning Google Cloud.
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“For now, saying ‘we’re multi-cloud’ safely means ‘we use AWS and Azure,'” Alex Brower, vice president of marketing at Cloud Academy, wrote in the report.
Industry analysts often suggest that GCP is the best product for data engineering. However, GCP did not even make it into the top 20 data engineering skills listed in job postings, while AWS and Azure did, the report found.
Here are the top 10 technologies listed in data engineering job descriptions, and the percentage of job descriptions they are listed in, according to Cloud Academy:
- SQL (65%)
- Python (64%)
- Spark (49%)
- Hadoop (43%)
- Java (43%)
- AWS (41%)
- Scala (24%)
- Kafka (23%)
- RedShift (20%)
- R (18%)
Kubernetes is also driving multi-cloud adoption, according to the report. As the number of public cloud platforms mentioned in job postings increased over the past three months, so did the mention of Kubernetes, suggesting that a multi-cloud strategy may necessitate adoption of containerization, the report noted.
The big takeaways for tech leaders:
- More companies are expecting DevOps engineers to be proficient in both AWS and Azure, while Google Cloud Platform is a distant third. — Cloud Academy, 2018
- SQL, Python, and Spark are the top skills needed to get a cloud data engineering job. — Cloud Academy, 2018