Top 10 Big Data Jobs

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Curated from datamation.com →

Thanks to high demand, big data engineers, data architects, data scientists and other big data experts are commanding top salaries.

1. Big Data Engineer
According to Robert Half data, people with the title “big data engineer” tend to earn more than anyone else involved with data management and administration. Salaries range from $126,250 (in the 25th percentile) to $212,500 (in the 95th percentile) with a median of $150,000.

While job responsibilities vary, big data engineers often oversee organizations’ analytics programs and work very closely with data architects, analysts and data scientists to help organizations obtain actionable insights from their data stores. As engineers, they also troubleshoot and optimize systems and software involved in data pipelines.

Typically big data engineers have at least a bachelor’s degree, and some have master’s degrees. To qualify for positions, you’ll likely need multiple years’ experience working with Hadoop and SQL-based databases, as well as the ability to program in R and Python.

2. Data Architect
Nearly as well-compensated as big data engineers, data architects often earn between $110,000 and $184,000 per year, with a median around $130,000.

Data architects need a combination of both business and technical skills. They need to understand what information business leaders hope to get from their data and then design and deploy the databases, data warehouses, data lakes and other systems the organization uses to manage and analyze its big data.
To qualify for these positions, you’ll need at least a bachelor’s degree, although some companies prefer a master’s. You also need multiple years of experience working with databases and data warehouses, and some employers look for job candidates who have used the specific software that they run.

3. Database Manager
Robert Half says that database managers typically make between $107,000 and $180,000 annually, with a median around $127,000.

Although the title makes it sound like they spend all their time with databases, database managers actually spend most of their time managing people. They’re responsible for overseeing the teams of IT professionals who deploy, manage, maintain, secure and troubleshoot the company’s databases. Of course, they also need up-to-date technical knowledge to make sure their team is following best practices and helping the business remain competitive.

Usually, database managers have at least a bachelor’s degree, plus experience working with databases and managing employees. Often, organizations will look for database managers knowledgeable about databases from a particular vendor, such as Oracle, Microsoft or IBM.

4. Data Scientist
Several publications have selected data scientist for their lists of the sexiest or most in-demand jobs in the current economy. Although demand for data scientists isn’t growing as quickly as it once was, Robert Half reports that they make between $100,000 and $168,000 with a median around $119,000.

Data scientists are masters of statistics. They clean and transform data, build models, apply algorithms and create visualizations that help business leaders make sense out of their big data.
For this job, you need an advanced degree — at least a master’s and probably a doctorate. You also need experience working with data and the ability to program in Python, Java, R and/or other languages. You need to understand advanced math, and you need to be able to communicate well so that you can explain your findings to your colleagues.

5. Database Developer
Like all developers, database developers tend to be well paid: between $97,750 and $164,500 with a median of $116,000.
As the name suggests, database developers write code related to databases. They need to have a very good understanding of SQL, and most know a couple of other programming languages as well.

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Yves Mulkers

Yves Mulkers is the founder of 7wData and a widely followed voice in the data and AI community. He curates the 7wData and AI Beat newsletters, reaching hundreds of thousands of data and AI professionals, and writes on data strategy, analytics, AI, and the evolving data ecosystem.