Whether it is easy to find a job in the big data industry or not is not just a _{matter of words and reality. You can get a general idea of ​​the recruitment needs and job requirements in the market.}

If you want to meet the company's employment standards, education, work experience, and mastery of skills are all very important~

Let’s first look at the report data of several recruitment websites:

• Released by Boss Zhipin , this spring’s recruitment data big data demand growth ranks second

• Liepin released the five fields with the fastest year-on-year growth in new jobs since 2019. The top five are: artificial intelligence, manufacturing, big data, medical care, and energy and environmental protection.

• The "2020 White Paper on the Development of China's Big Data Industry " shows that in 2019, the scale of China's big data industry reached 539.7 billion yuan, a year-on-year increase of 23.1%, and then grew steadily. It is expected to exceed one trillion yuan by 2022.

• According to the statistical results of LinkedIn, CCID Think Tank, Lagou.com and other institutions, the overall gap of data talents in the era of big data is showing a growing state of intensification. In the past three years, the data talent gap has been increasing by 500,000 people per year. It is estimated that in 2022, after college graduates majoring in big data enter the job market on a large scale, the growth rate of the overall gap will slow down, but this gap is still will exist for a long time.

Recruitment is available, but applicants often encounter various problems in finding a job because of their academic qualifications and work experience. So what is the specific situation of developers who have been engaged in big data now? Let's look at the following aspects:

1. Academic level

From the perspective of education level, the education level of my country's big data talents is divided into 4 categories, namely master's degree and above, bachelor's degree, junior college, and junior college, among which the big data talents with bachelor's degree are the most, accounting for as high as 65.45%. Followed by master's degree and above, and big data talents with junior college degree and below account for only a small part. It can be seen that the big data industry, as an emerging industry, generally has relatively high educational requirements for talents.

2. Professional source

In terms of professional sources, the professional sources of big data talents in my country are mainly composed of four major categories: mathematics and science, economic management, computer and other majors, of which computer science accounts for the highest proportion, followed by mathematics and science.

3. Channel source

The channel sources of big data talents are divided into four categories, namely school recruitment, social recruitment, internal training and recommendation, and training institution recruitment. See the figure below for the number and proportion of the sources of big data talents in enterprises.

Among them, social recruitment accounts for the largest proportion, which is higher than the sum of school recruitment, internal training and promotion, and training institution recruitment. At present, it mainly relies on social recruitment, which shows that school education is out of touch with social needs, and internal training and training cannot meet job requirements.

4. Salary level distribution

At present, the salary of big data talents is at a relatively high level. Salaries below 10,000 yuan accounted for 34.6% of the total; 10,000 to 20,000 yuan accounted for 35.64%; and above 20,000 yuan accounted for 29.77%.

5. Type and number of posts

At present, the big data positions provided by enterprises can be divided into the following categories according to the job content requirements:

① Primary analysis category, including business data analysts, business data analysts, etc.

② Mining algorithms, including data mining engineers, machine learning engineers, deep learning engineers, algorithm engineers, AI engineers, data scientists, etc.

③ Development and maintenance, including big data development engineers, big data architecture engineers, big data operation and maintenance engineers, data visualization engineers, data acquisition engineers, database administrators, etc.

④ Product operation category, including data operation manager, data product manager, data project manager, big data sales, etc. The number and proportion of the four types of posts are shown in the figure below.

The demand for big data is increasing, and the country is also opening related jobs, which have increased year by year since 2018.

At this time, students and parents who apply for university are also very interested in big data and artificial intelligence. Big data has entered the top 5 for three consecutive years, and a bachelor's degree is all that is required.

In the foreseeable next few years, this is really a sunrise industry, and there is a big gap now.

So if you want to know what kind of job you can find in the future and the salary of the job, let us show it in the form of data~

Then open Boss direct employment, search for big data engineers:

let's do data analysis:

The salary column has a minimum salary and a maximum salary. We compared and analyzed different cities and found that Beijing has the highest salary level, with the lowest being 22k and the highest being 38k.

Working years are also a big factor that restricts salary levels. It can be seen from the figure that even if you have just graduated, you can reach a salary range of 11-20k.

As far as educational requirements are concerned, most of them are undergraduates, followed by junior colleges and masters, and others are so few that they are not shown in the figure.
Most of the requirements of enterprises for different positions are 3-5 years. Of course, enterprises need employees with certain work experience, but in actual recruitment, if you have project experience and no problem with theoretical knowledge, enterprises will relax the conditions.

Analyzing different industries, we found that the demand for big data jobs is distributed in all walks of life, mainly in computer software and the Internet, and it may also be determined by this recruitment software. After all, Boss direct employment is still mainly in the Internet industry.

Let's take a look at which companies are recruiting for big data-related positions. Judging from the number of more than 15, Huawei, Tencent, Ali, Byte, these big companies still have a large demand for this position.

So what skills do these jobs require? Spark, Hadoop, Data Warehouse, Python, SQL, Mapreduce, Hbase, etc.

According to the domestic development situation, the future development prospects of big data will be very good. Since enterprises have started digital transformation in 2018, the demand for talents in the field of big data in first- and second-tier cities is very strong. In the next few years, the demand for talents in third- and fourth-tier cities will also increase significantly.

In the field of big data, domestic development is relatively late. Since 2016, only more than 200 universities have opened majors related to big data, which means that the first batch of graduates in 2020 have just entered the society. There is an urgent need for big data talents but insufficient talents, so there will be many employment opportunities in the big data field in the future.
High salaries and large gaps naturally become the "salary" choice for professionals in the workplace!

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Getting Started with Big Data Development in Phase 1

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MySQL is the entire IT basic course, and SQL runs through the entire IT life. As the saying goes, if SQL is well written, you can find a job easily. This course fully explains MySQL8.0 from zero to advanced level. After studying this course, you can have the SQL level required for basic development.

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Hadoop offline is the core and cornerstone of the big data ecosystem, an introduction to the entire big data development, and a course that lays a solid foundation for the later Spark and Flink. After mastering the three parts of the course: Linux, Hadoop, and Hive, you can independently realize the development of visual reports for offline data analysis based on the data warehouse.

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This course will establish a group data warehouse, unify the group data center, and centralize the storage and processing of scattered business data; the purpose is from demand research, design, Version control, R&D, testing, and launch, covering the complete process of the project; digging and analyzing massive user behavior data, customizing multi-dimensional data sets, and forming a data mart for use in various scene themes.

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The fourth stage PB memory computing

Pre-study guide: Spark has officially adopted Python as the first language on its homepage. In the update of version 3.2, it highlights the built-in bundled Pandas; Spark content.

1. From entry to mastery of python (19 days)

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3.spark3.2 from basic to proficient

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For the first time, the entire network disclosed the actual combat of big data Spark offline data warehouse industrial projects, and Hive+Spark built an enterprise-level big data platform