The skills that a big data development engineer needs to have are as follows:

Simply put, a big data engineer is responsible for creating and maintaining data analytics infrastructures, which includes the development, building, maintenance, and testing of big data architectures, such as databases and big data processing systems. Additionally, a Big Data Engineer is also responsible for creating processes for modeling, mining, acquiring, and validating data collections, among other things.

1, big data architecture tools and components

Enterprise big data framework, mostly choose to realize the framework based on open source technology, which includes Hadoop, Spark, Storm, Flink based on a series of component frameworks, and its ecosystem components.

2, in-depth understanding of SQL and other database solutions

Big Data engineers need to be familiar with database management systems, in-depth understanding of SQL, as well as other database solutions, such as Cassandra or MangoDB must also be familiar with, because not every database is built by recognizable standards.

3. Data warehousing and ETL tools

Data warehousing and ETL capabilities are critical for Big Data engineers. Data warehousing solutions like Redshift or Panoply, as well as ETL tools like StitchData or Segment are very useful.

4. Hadoop-based analytics (HBase, Hive, MapReduce, etc.)

An in-depth understanding of Apache Hadoop-based data processing frameworks is required, with at least HBase, Hive, and MapReduce knowledge stores necessary! .

5, coding

Coding and development skills is an important requirement as a big data engineer, the main mastery of Java, Scala, Python three languages, which is very critical in the big data.