1. Big data architecture stuff and components

Enterprise big data structure is mostly picked based on the open source skill structure, which contains a series of component structures based on Hadoop, Spark, Storm, Flink, and its ecosystem components.

2. Deepen your understanding of SQL and other database solutions

Big Data engineers need to understand the database processing system and deepen their understanding of SQL, and the same with other database solutions such as Cassandra or MangoDB, which must be understood, because not every database is built from recognizable standards.

3. Data warehousing and ETL stuff

Data warehousing and ETL skills are critical for Big Data engineers. Data warehousing solutions like Redshift or Panoply, and ETL stuff like StitchData or Segment are very useful.

4. Profiling according to Hadoop

Deep understanding of data processing structures according to Apache Hadoop is required, and at least a store of knowledge of HBase, Hive, and MapReduce is necessary.

5. Coding

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