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Highest Paying Data Science Jobs in the World

Knowledge Hut

While only 33% of job ads specifically demand a data science degree, the highly sought-after technical skills are SQL and Python. Data Architect ScyllaDB Data architects play a crucial role in designing an organization's data management framework by assessing data sources and integrating them into a centralized plan.

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R Hadoop – A perfect match for Big Data

ProjectPro

When people talk about big data analytics and Hadoop, they think about using technologies like Pig, Hive , and Impala as the core tools for data analysis. R and Hadoop combined together prove to be an incomparable data crunching tool for some serious big data analytics for business.

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Big Data Engineer Salary - How Much Can You Make in 2023?

ProjectPro

Mid-Level Big Data Engineer Salary Big Data Software Engineer's Salary at the mid-level with three to six years of experience is between $79K-$103K. Knowledge and experience in Big Data frameworks, such as Hadoop , Apache Spark , etc., As a result, there is a difference in the Big Data Engineer's salary by the skill-set.

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Top Big Data Certifications to choose from in 2023

ProjectPro

If your career goals are headed towards Big Data, then 2016 is the best time to hone your skills in the direction, by obtaining one or more of the big data certifications. Acquiring big data analytics certifications in specific big data technologies can help a candidate improve their possibilities of getting hired.

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How to grab the high-paying jobs in todays Big Data and Cloud Computing field?

ProjectPro

We have gathered the list of top 15 cloud and big data skills that offer high paying big data and cloud computing jobs which fall between $120K to $130K- 1) Apache Hadoop - Average Salary $121,313 According to Dice, the pay for big data jobs for expertise in hadoop skills has increased by 11.6% from the last year.

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Data Scientist Salary-The Ultimate Guide for 2023

ProjectPro

Unlike other kinds of data specialists who specialize in a specific task (such as data engineers and data analysts ), data scientists tackle the end-to-end lifecycle of a data science project right from data acquisition to model optimization to communicating insights to stakeholders.

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