How to Become Big Data Engineer
Due to the current lack of big data talent, since 18 years is the first year of each university to set up large data professional, it does not have the relevant professional expertise in big data into society. For the company, it is difficult to recruit the right people.
Alibaba has held a big race data, to motivate internal staff through this contest, also found outside talent, so that all sectors of big data engineer emerge. Daren various fields just have to learn to use the data, the data can also be a great engineer.
If ever there are no major data relevant experience and would like to join this large data-paying industry that a lot of people will choose to learn through systematic training, in order to truly enter into the big data-paying industries. But in today's society a wide range of training institutions, training content also has many different, we carefully choose be sure to keep their eyes open, to avoid the wrong result in personal financial loss.
Remuneration as IT occupations in the "Panda", engineer of large data treatment of the income can be reached top class. According to observation, the domestic IT, telecommunications, industry recruitment, 10% of all relevant data and large, and the proportion is growing. "The arrival of big data era is suddenly in the domestic development momentum aggressive, but talent is very limited, is now completely in short supply situation." In the United States, large data engineers an average annual salary of $ 175,000, and it is understood in the domestic top Internet companies, pay the same level of large data engineers may be greater than other high positions 20-30 percent, and popular business seriously.
Career Paths Internet technology development booming, the era of artificial intelligence, grabbed the next outlet. To help those who want to switch the direction of the Internet want to learn, but because of lack of time, lack of resources and give up. I am finishing a new big data and advanced data Advanced Development Guide, big data study group: 957 205 962 can be found in Advanced Organizational Learning welcome and want to delve into the big data small partners to join due to the small number of big data talent Therefore most of the company's data sectors are generally flat hierarchical model, roughly divided into data analyst, senior research fellow, department director of three levels. Large companies may apply in accordance with the dimensions of the field to divide the different teams, and in the smaller companies will need to wear many hats. Some big data strategy with special emphasis on Internet companies will set up another top job - as chief data officer of Alibaba. "Most people in this position will be to develop research, data has become an important strategic talent." On the other hand, large data engineer understanding of the business and products, and no less than the business sector employees, it can also be turned to products or marketing Department, and even rose to the senior management of the company.
In a sophisticated data-driven company, "Big Data Engineer" is often a team, which means that from the data collection, collation presentation, analysis and business insight, so that the whole process of market transformation. The team might include the role of data engineers, analysts, Product Specialist, Marketing Specialist and business decision makers together to accomplish business value from raw data to the converted - In general terms, this is a support enterprises to make business decisions, discover business important group mode.
A good big data engineer to have a certain logic analysis capability, and can quickly locate a business problem of key attributes and determinants. "He had to know what is relevant and what is important, what kind of data is the most valuable use, how to quickly find the core needs of each business." The United Nations Joint Laboratory data Baidu large data scientist Shen Zhiyong said. Ability to learn can help large data engineers to quickly adapt to different projects, and data in a short time become experts in the field; the ability to communicate allow them to carry out the work more smoothly, because large data engineer working mainly divided into two ways : driven and data-driven analysis department, the former often need to understand the development needs of product managers, who need to find operations informed the actual data model transformed by the marketing department.
你可以将以上这些要求看做是成为大数据工程师的努力方向，因为根据万宝瑞华管理合伙人的观察，这是一个很大的人才缺口。目前国内的大数据应用多集中在互联网领域，有超过56%的企业在筹备发展大数据研究，“未来5年，94%的公司都会需要数据工程师”
大数据工程师做什么？
用阿里巴巴集团研究员薛贵荣的话来说，大数据工程师就是一群“玩数据”的人，玩出数据的商业价值，让数据变成生产力。大数据和传统数据的最大区别在于，它是在线的、实时的，规模海量且形式不规整，无章法可循，因此“会玩”这些数据的人就很重要。
如果把大数据想象成一座不停累积的矿山，那么大数据工程师的工作就是，“第一步，定位并抽取信息所在的数据集，相当于探矿和采矿。第二步，把它变成直接可以做判断的信息，相当于冶炼。最后是应用，把数据可视化等。”
因此分析历史、预测未来、优化选择，这是大数据工程师在“玩数据”时最重要的三大任务。通过这三个工作方向，他们帮助企业做出更好的商业决策。
找出过去事件的特征大数据工程师一个很重要的工作，就是通过分析数据来找出过去事件的特征。比如，腾讯的数据团队正在搭建一个数据仓库，把公司所有网络平台上数量庞大、不规整的数据信息进行梳理，总结出可供查询的特征，来支持公司各类业务对数据的需求，包括广告投放、游戏开发、社交网络等。
找出过去事件的特征，最大的作用是可以帮助企业更好地认识消费者。通过分析用户以往的行为轨迹，就能够了解这个人，并预测他的行为。“你可以知道他是什么样的人、他的年纪、兴趣爱好，是不是互联网付费用户、喜欢玩什么类型的游戏，平常喜欢在网上做什么事情。”腾讯云计算有限公司北京研发中心总经理郑立峰对《第一财经周刊》说。下一步到了业务层面，就可以针对各类人群推荐相关服务，比如手游，或是基于不同特征和需求衍生出新的业务模式，比如微信的电影票业务。
预测未来可能发生的事情
通过引入关键因素，大数据工程师可以预测未来的消费趋势。在阿里妈妈的营销平台上，工程师正试图通过引入气象数据来帮助淘宝卖家做生意。“比如今年夏天不热，很可能某些产品就没有去年畅销，除了空调、电扇，背心、游泳衣等都可能会受其影响。那么我们就会建立气象数据和销售数据之间的关系，找到与之相关的品类，提前警示卖家周转库存。”
在百度，支持“百度预测”部分产品的模型研发，试图用大数据为更广泛的人群服务。已经上线的包括世界杯预测、高考预测、景点预测等。以百度景点预测为例，大数据工程师需要收集所有可能影响一段时间内景点人流量的关键因素进行预测，并为全国各个景点未来的拥挤度分级—在接下来的若干天时间里，它究竟是畅通、拥挤，还是一般拥挤？
找出最优化的结果
根据不同企业的业务性质，大数据工程师可以通过数据分析来达到不同的目的。
以腾讯来说，郑立峰认为能反映大数据工程师工作的最简单 直接的例子就是选项测试（AB Test），即帮助产品经理在A、B两个备选方案中做出选择。在过去，决策者只能依据经验进行判断，但如今大数据工程师可以通过大范围地实时测试—比如，在社交网络产品的例子中，让一半用户看到A界面，另一半使用B界面，观察统计一段时间内的点击率和转化率，以此帮助市场部做出最终选择。
作为电商的阿里巴巴，则希望通过大数据锁定精准的人群，帮助卖家做更好的营销。“我们更期待的是你能找到这样一批人，比起现有的用户，这些人对产品更感兴趣。”一个淘宝的实例是，某人参卖家原来推广的目标人群是产妇，但工程师通过挖掘数据之间的关联性后发现，针对孕妇群体投放的营销转化率更高。
需要具备的能力
逻辑思维能力强
计算机编码能力
特定应用领域或行业的知识
大数据技术学习主要是分三部分
一、编程基础
二、大数据技术
三、实训项目（真实的大数据项目）