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Five must have data engineering skills. Number one, apache hadoop: apache hadoop has seen tremendous development over the past few years. Its components, like hdfs pig, mapreduce hbase and hive, are currently in high demand. Number two. Nosql: nosql databases are better equipped with meeting data access and storage needs for companies. Nosql databases like mongo, db and crunch base are now rapidly replacing traditional sql databases like oracle and db2. Big data engineers with experience in Nosql are in immediate demand in most places in the united states. Number three setting up cloud clusters: Given the acute reliability that big data places on networks, a lot of work is outsourced to the cloud to avoid the hassle. Cloud clusters also make it easier for engineers to crunch large volumes of data to discern patterns. Being well versed with setting up cloud clusters can give tremendous growth opportunities in prominent multinational companies. Number four machine learning: Machine learning and data mining make an important contribution to the field and are some of the most prominent components. Developing expertise in these fields can help big data engineers in developing classification recommendation and personalization systems. This engineers are in high demand in service based companies. Number five apache spark: Apache spark is extremely popular in roles involving big data analytics, a quicker and more straightforward alternative for complex framework like map reduce the increase of sparks in memory. Stack has also made the skill extremely sought after.