With the fall school recruit came to an end, all kinds of online recruitment has also been distributed data, big data industry engineers average monthly salary of 11,600 yuan to lead the country to become "super high salaries, the tall," a synonym. If you study large data relevant professional, then congratulations, your development opportunities come, if you want to switch to big data is not too late. This article will use more than 70,000 jobs from big data worry-free future recruitment job sites collect information, analyze the current big data hottest employment and development orientation and skills needs, to help students and related professionals who want to switch large data were white workplace find their own career goals and direction of development, has become the era of big data jobs "favorite" to achieve the dream of high-paying, to the pinnacle of life!
Data Description:
One, Big Data industry a bright future
Data source: Baidu Index
, "New York Times" said that in 2012, once wrote a column, "big data" Time has come, in the commercial, economic and other areas, decisions will increasingly be made based on the data and analysis, rather than based on experience and intuition. With the development of the Internet and information industry in recent years, the amount of data is accelerating the expansion, more and more people realize the importance of data for the enterprise. "Big Data" as shown in the figure from the Baidu search frequency can be seen from its search popularity began to grow rapidly in 2012, the country experienced after a 2017 outbreak years, still continue to be widespread concern.
Source: Institute for Industrial Commercial
With the rapid development and implementation of artificial intelligence National data strategy, cloud services, networking and other industries, China's large-scale data industry is showing increasing year by year, is expected to reach 800 billion by 2021 yuan. At the same time, the share of data types from the perspective of Things and other great vitality large data types will grow significantly for large enterprise data brought new development opportunities.
The rapid development of the industry means a huge demand for qualified personnel. According to Tsinghua University joint workplace social platform LinkedIn (LinkedIn) released the "digital transformation of the Chinese economy: talent and employment" report shows that in 2018 our country talent gap large data field of up to 1.5 million by 2025 will reach 2 million . To meet the demand for talent, the major domestic colleges and universities have begun to set up large data scientific data and technical expertise, which means that in the future there will be big waves Big Data professionals influx of talent market, how can a foothold in the field of big data and there is a good develop it?
Second, the large data analysis jobs
because of big data in related fields and a lot of skills, job search a variety of "big data" will get a wide variety of on any job site, such as data analysts, data architects big, big data development engineers and many more. Now we will do this in-depth analysis and interpretation to help people find their own position and career goals for their own development.
First, since the level of big data industry in different regions are at different stages, the standard for positioning requirements and salaries and other types of jobs data taken is not uniform and may even exist essential differences. In order to provide advice instructive to the reader, this article intends to focus more leading industry Big Data, abundant talents city, the city's business needs such information for big data talent developed relatively mature and standardized, more representative and be analytical, that readers more instructive job reference.
Source: "2019 China Industry Development White Paper on big data,"
according to a joint alliance of large data industry ecosystem CCID Consulting completed the "2019 China Industry Development White Paper on big data" shows that the data nationwide talent focused on the first-tier cities. Beijing, Shanghai, Shenzhen, Hangzhou, Guangzhou is the development of information technology leader, Ali, Baidu, Tencent, drops, the US group, millet and other Internet companies established and emerging companies are unicorns gather in these five cities, these cities have development of large industrial soil data, gathered and nurtured a large number of big data talent; while the high level of these five urban economic development, good corporate remuneration, large enterprises and high data aggregation, providing a full range of conditions for personal growth, to attract and keep live large number of senior personnel as well as large data nationwide large data relating to graduates. By the end of 2018, nationwide core personnel data of about 200 million people, accounting for big data talent sum of these five cities reached 47.5%, a large talent pool of data belongs to the first echelon.
In addition, we also found that the search results include a lot of relevance to "big data" is not large or name rather ambiguous position. Such as data analysis jobs Commissioner, although in great demand, but from the perspective of job requirements do not involve a lot of data processing and analysis, and data associated with the large technical requirements. Another assistant, consulting, design, processing to delete this article do not discuss the specific process is as follows.
1, Big Data era who is the most popular? Who is the highest paid?
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first from the demand point of view, big data development engineer is undoubtedly the most popular posts, followed by data analysts, both demand accounted for 28.7% and 25.8%, respectively, taking more than half of total demand. In third place, the algorithm engineers, 8.9% of the total demand, followed by a product manager. Architecture, database development, operation and maintenance and data mining engineer similar demand, were down 4%, relatively low. Minimum requirement is the database administrator, accounting for only 1% of total demand.
Salary data are usually in the range form (such as 1.3-2.5 Wan / month) release, so this calculation the average of the minimum wage and maximum salary for each job given to reflect the remuneration. From the results, the algorithm salaries of engineers and data architects the highest average monthly salary respectively 21-35k, 23-34k, but at the same salary algorithm engineer span is also larger, may be closely related to working life; data analysis Although demand for the division's second-largest, but the minimum wage range, but the average minimum monthly salary 12k; by contrast, the greatest demand for development engineer salary levels is very impressive, a monthly salary between 14k to 22k.
2, good development is the absolute principle
believe the data read these needs and treatment, you've got the heart of positions. But its possible future development is how, it is appropriate to long-term development? But also I want to have the kind of transformation hardware conditions? His career is a marathon, not a sprint, you want to achieve promotion and pay rise, the dream of a million a year, we must have a plan and goals in order to be more motivated, directionally learn and gain experience and resources, let yourself grow up fast in the big data industry. Based on this, the following salary and job requirements from the perspective of the development prospects of hot jobs to do in-depth analysis, hoping at the same time providing jobs, and some thinking about long-term career planning can lead to readers.
First of all, jobs in different directions of development of core technologies have different demands and positions, so before doing thorough inquiry, it is necessary to classify jobs according to popular demands. This paper summarizes the discovery of these hot jobs can be mainly attributed to business-direction data analysis, as well as more technical type of data mining, development / R & D and the operation and maintenance of four kinds of employment direction.
Seniority vs demand papers
Companies have different qualification requirements for the same jobs, some jobs and not much room for development. Therefore, from a long-term point of view, the transition intend to do promotion. Based on this, we start to analyze corporate demand for talent in different qualifications of each job, and summarizes some of the characteristics of jobs.
Big Data Architect, Product Manager, Big Data Platform Development Engineer: high-end post
direction for this type of job requires a higher experience, is a large industry data more senior positions, that is a long-term development or promotion may want to consider . As can be seen from the figure heat, mainly focused on the needs of the majority of jobs have 3 - 4 years of experience in personnel, and architects focused on 5--7 years of experience, and accounting for 61.3%, but only for 1--2 years only 2% of working experience seekers, demand, showing that the job is the most valued work experience. Big Data platform product manager and development engineer of demand is concentrated in the more than three years.
Getting friendly Position: data analysts, database administrators, database operation and maintenance engineers and development engineers
this type of job a higher demand for talent shorter work experience, is starting a new job or career change direction you want big data can be considered. For the minimum work experience requirements are data analysts, nearly 50% of the jobs demand only requires 1--2 years work experience. Although low barriers to entry, but the continued development of the job is relatively low, most of the low level of business for senior data analyst needs, so competition will be larger. Above in perspective, consider the development of long-term perspective can belong to the product line manager for the business type.
In addition, the database administrator, database development, and operation and maintenance engineer for the threshold of experience required is relatively low, more than 10% of demand requires only one year of experience, more than three percent require only 1--2 years work experience. But with respect to the data analyst, the three main entry job-friendly demand is concentrated in the 3--4 years of experience, especially in senior-level database administrator for talent also has nearly 25% of demand, it can be said that employment line the vertical development is very high.
Pay rises articles
So, if sustained development in the same route, wages up the number? This is also an important factor that when we do career planning will consider, let's do a detailed analysis of salary increases (hereinafter collectively referred to as 1, 2 years experience for entry-level, 3--4 years for the intermediate, 5--7 years for the senior class) .
Data mining direction:
First of all, the highest entry-level positions in the direction of data mining job salary, salary increases and faster, always better than the other positions in addition to the architect, the work will be the second year higher than the average pay of 4,000 yuan treatment, which is all positions the same level of salary increment largest. After Specifically, the number of junior engineers dug average monthly salary of up to 14,306 yuan, while the average monthly salary of junior engineers algorithm is even higher, reaching 18,410 yuan, as long as one year of work experience is expected to get close to or even more than other post for three or four years salary. This no doubt explains the scarcity of talent the highest data mining direction in these areas.
Data analysis direction:
Product Manager is the next highest starting salary jobs, primary level can get an average monthly salary of $ 14,000. But compared to other positions, product manager of slower wage growth, average monthly salary of only $ 15,000 in the second year of work. Only reached 3-4 when experience will have a substantial pay rise, with an average of up to $ 21,000 / month, after reaching a senior level, only a raise of 2,200. On the other hand, belong to the same analysis data analyst direction, despite their lower starting salary for primary, the average monthly income is only $ 10,000, but with seniority salary growth is faster, more stable, beginner to intermediate average pay of 3,000 yuan, and senior data analyst although large demand for small competition, but the average monthly salary of up to 26,000 yuan. But note that, due to different enterprises, it is called, a senior analyst may be biased towards data mining, salaries shown above is approaching, it may be compared to the beginning, intermediate and more biased in favor of technology-based.
Development / R & D direction:
in the development of class data architect jobs pay the most impressive, with 2 years experience in entry-level positions average monthly salary of up to 23,475 yuan, even higher than with 5 - Other operation and maintenance positions 7 years of experience. But the value of the job work experience, 1 - Low demand for talent 2 years of experience, and almost one year of experience will not accept the job seekers. And despite the high starting salary, architect salary growth slow.
Big Data Platform Development Engineer salary level and growth is slightly better than database development engineers, but both very close, entry-level positions pay between 11,000-14,000, from beginner to intermediate average wage increase 1,500-17,000 yuan, the average senior posts mentioning pay 5000-6000 dollars.
Operation and maintenance management direction:
operation and maintenance engineers and database administrators starting salary is the lowest, the average entry-level salary of less than $ 10,000. However, operation and maintenance engineers a month in the second year there will be more substantial pay rise, an increase of 43 percent salary increase after the median income for 13,642 yuan, but also more substantial. At the same time with the increase in both jobs qualifications, intermediate and senior levels will reach similar or slightly lower than the level of development engineers.
3, you see these promising positions
believe that the above analysis looked at, you already have a preliminary plan of its own target position or direction. Next, we went from academic and technical capacity to analyze two aspects, to achieve career goals what "hardware" requirements.
Academic articles - to fight the fight diploma or experience?
When the job is usually academic background business very fancy, whether I can support my academic career goals a few years later? You can substitute or compensate for inadequate education through work experience? Next, let's clear these points by analyzing the relationship between the four categories of jobs work experience and qualifications required.
First, the direction of data analysis, with the increase of qualifications, enterprise for College and Below preferences significantly reduced, showing the importance of experience is difficult to replace a diploma. In particular data analyst, reduced from 40% of primary demand to 5%, so although good entry, but want to develop in this direction is necessary to have a college diploma. But both positions mainly prefer bachelor's degree, a bachelor of the background jobs to meet the needs of more than 95%. Wherein the master data analysts and above although for preference relatively high, but only 3% -4%, and if you want to work as described above, product manager, educational background is absolutely enough.
Not difficult to see from the chart, salary data mining direction, although the best, but also of the highest academic requirements. First is easy to see the two posts of master's degree or above preferences are strong, and the high barriers to entry. Only one year of work experience digging post number 12% of the demand requirement doctoral degree, master's degree or above nearly 20%. But the long-term development, which demands a higher degree (diversification) is possible through relevant work experience to be replaced. Easy to see that with the increase of qualifications, enterprise for master or doctoral degree reduced demand for highly educated is not so value the.
On the other hand, the algorithm engineers have more than three percent of the primary job requirements demand a master's degree. Although with the increase in work experience, business tends to weaken the preference for highly educated, but still more than 25%. Visible algorithm in order to engineer the direction of development, has a master's degree is preferred.
Big data development direction of the three main positions academic requirements less stringent, undergraduate background is the main demand. Junior architect may require a master's degree, but the main demand of the jobs are concentrated in 5--7 years of experience, a master's degree needs only 1%. Databases and data platform development engineer for post-secondary education and below the demand increase and decrease, although with qualifications, but little difference between senior and junior level, and therefore more emphasis on relevant experience in development / R & D direction posts, qualifications only as an entry-level threshold, impact on the long-term development is not large.
In comparison, operation and maintenance jobs on the academic requirements relative direction of the most liberal, most entry-level jobs open academic requirements, more than half of the primary database administrators only require a college education, primary operation and maintenance engineers, nearly half of such demands. From the long-term development perspective, the former candidate for the needs of such backgrounds have been declining, but there are still more than a quarter of senior positions do not require college degrees. The latter is a large reduction ratio, from 46% to 17%, easily visible entry in this direction, but if the long-term development of operation and maintenance engineers would be more pick qualifications.
Skill - data analysis and data mining class
First, on the whole, Python is a data analysis and data mining class positions most used analysis tool, followed by the R language, SQL databases is the main tool.
Specifically, in the four partial type of business analyst and product manager positions lower frequency of mention computer skills. For product managers, use the most is the use of interactive design software Axure, followed by a flow chart / mind mapping tools to Visio, XMind and MindManager based, in addition to 5% of the demand mentioned PPT and SQL skills. Data Analyst skill requirements focus on a variety of analytical tools, most notably Python, followed by Excel and R, a small part of the job requirements will use SAS, SPSS and visualization tools Tableau.
Data mining engineers need more programming skills, need to have Python / R / Java / Scala, and requires Hadoop / Spark of engineering experience, proficient in SQL / Hive is a must. Roughly the same algorithm engineer and several engineers dug skill system, in addition to the demand for basic programming Java and C ++ some more.
Skill - big data development and operation and maintenance class
First, the development of key skills and job requirements of the operation and maintenance of a large degree of overlap direction, SQL / MySQL is an essential skill, proficiency in the use of the Linux operating system is also essential, but different focus positions using each tool.
Development engineers and architects requirements for Hadoop, Spark platform and Spring, Hive, HBase and other tools of higher development language mainly using Java, Python for preference is not high, the difference is the development engineers compare the reference rate Redis database high, operation of the system architect to Kafka reference rate is relatively high. DBAs and database development positions lower reference rate for big data platform and various components, skill requirements are relatively concentrated in the familiar MySQL / Oracle database, Linux operating system, and Shell Programming. If you want to shift to other routes, then, we need to add practical experience related to the Hadoop platform. Operation and maintenance engineers in the middle position, more comprehensive skill requirements, so the skill level if the transition in the other direction is relatively easy.
Summary
To summarize the above analysis, data analyst is more suitable for programming weak, big business talents partial data entry type jobs, and businesses of their great demand, job seekers need to be appropriate to add several Python, Excel, R, etc. analysis experience in using the tool. In the long run if you want to develop the best product manager direction reflects the interaction design and application flowcharting tool in your resume; if you want to data mining direction, then the underlying want to collect, store data and computing tools to expand the technical capacity .
Getting data mining engineer more suitable domain expertise, we have a master's degree technical personnel. Lack of academic background, it accumulated in the relevant work experience required, but also can make up for lack of qualifications. Long-term point of view, the number of engineers dig if you want to engineer the algorithm development, the need for more solid low-level programming capability, high academic requirements while also reflects the algorithm engineers need a strong theoretical capacity and inquiring mind.
Development Engineer is more suitable for the existing Java development experience and technical personnel to switch large target position data, and the job is currently a great demand. Long-term development can be developed to the architect, on the skills and qualifications are not too many to make up, is the major need of work experience. This audience may wish to try different contact groups, architecture and technology, in order to exercise the design architecture, leadership and communication skills, you can start to contact the consulting industry more diversity issues and team, full gain experience. Operation and maintenance personnel and database can also be transferred to do the development, technical aspects need to add Java programming skills, followed by knowledge of Hadoop platform, and preferably has a bachelor's degree.
As the saying goes, "Men fear into the wrong line," big data industry, although popular, that we should not follow the crowd to follow the style, but the first to see the higher perspective of enterprise development and job demand routes, combined with personal capacity good career planning. Targeted school or job, in order to accumulate experience in itself conducive to long-term development, to find the most suitable for their posts, go higher in the era of big data, farther!
