2014 eight hottest Big data jobs

Large data age, data surplus, talent shortage, more and more IT professionals want to be able to enter the big data fields full of opportunities, but, in the end what is the specific large data professional positions and talent most popular? Human Resources company Kforce recently released a report of the top ten largest data jobs (annual salary) for 2014 years according to IT professional remuneration:

I. ETL developer (11.13 million USD)

With the increasing of data types, the demand for data integration professionals is more and more vigorous. ETL developers interact with different data sources and organizations, extract data from different sources, transform and import data warehouses to meet the needs of the enterprise.

ETL software industry is relatively mature, the relative position of the work life cycle is relatively long, usually by the internal staff and outsourcing contractor to complete. One of the reasons why ETL talent is hot in the big Data age is that Hadoop is just the Poor's ETL in the early stages of big data applications.

Second, Hadoop developers (15-17.50,000 USD)

Hadoop is an open source framework based on Java, with the data set growing, and traditional BI data processing cost is too high, enterprises on Hadoop and related low-cost data processing technology such as Hive, HBase, MapReduce, pig, and so on will continue to grow. Today's technicians with the Hadoop framework experience are the most sought-after large data professionals.

Three, large data visualization tool Developer (15-17.50,000 USD)

The analysis of massive data is a big challenge, and new data visualization tools such as Spotifre,qlikview and tableau can display data visually and efficiently. In the past, data visualization was a business intelligence developer category, but with the rise of Hadoop, data visualization has become an independent professional skill and position.

Iv. data scientists (USD 12.14 million)

Formerly known as data Architects, data scientists are a new type of work that translates enterprise data and technology into business value. Data scientists should first have excellent communication skills and be able to interpret data analysis results to both it and business leaders.

In general, data scientists are a combination of analysts and artists and require a variety of interdisciplinary and business skills.

V. OLAP developer (9.8-116,000 USD)

OLAP Online Analytics developer, who is responsible for extracting data from relational or relational data sources to build models, and then creating a user interface for data access to provide high performance predefined query capabilities.

VI. Data Warehouse integrated machine expert (9.8-124,000 USD)

Such experts are familiar with the large data integration machines of Teradata, Neteeza and Exadata. Ability to perform data integration, management, and performance optimization on these all-in-one machines.

Vii. Predictive Analysis Developer (USD 10.13 million)

The marketing department often uses predictive analysis to predict user behavior or lock target users. Predictive analytics developers have some scenarios that look like some kind of data scientist, which tests thresholds and predicts future performance based on enterprise historical data.

Viii. Information Architect (11.4-135,000 USD)

Big data has sparked a revival in master data management. It requires very professional skills to fully develop and support decision making to use enterprise data. Information architects must understand how to define and archive key elements to ensure data management and utilization in the most efficient manner. Key Skills for information architects include master data management, business knowledge, and data modeling.