5 Lucrative Careers a Hadoop Certification can Get You
Technology is bringing about seismic changes to every aspect of our lives and 2018 will be the year where we will see Robot chefs, AI doctors, self-driving cars and deliveries being carried out by drones. The recently released Robert Half 2018 Salary Guide for Technology Professionals mentions that 67% of technology executives consider Big Data, Data Science Cloud, Mobile and Digital Marketing initiatives as the greatest contributing factors to hiring in 2018.The “Big Data” revolution is here and it is safe to say that the most important and lucrative new technology careers across various industries belong to professionals who know how to work with big data using tools like Hadoop and Spark(two of the leading big data framework used by Fortune 500 companies).
According to Gartner, many organizations have invested in diverse big data projects but are stuck in the very pilot stage because the learning curve and required level of expertise per industry and use case is challenging for IT professionals. Big data jobs are red hot and professionals should consider a career in this cutting edge IT field. Employers are recognizing the value of Hadoop and Spark skills as they scramble to fill multiple open positions. There is lot of discussion within the big data community about the emerging big data technologies like Hadoop, Spark, Kafka and more. The demand for these technologies is leaving professionals confused on what are the top rewarding career options available for anyone having a Big Data Certification on their resume. There are several career paths you can take and a multitude of big data job roles that utilize these skills, just consider one of these top 5 data-centric jobs for a rewarding big data career –
1) Hadoop Developer
A hadoop developer job role is synonymous to that of a software developer but in the big data domain. Hadoop developer actually codes or programs big data applications. A hadoop developer knows which hadoop component to choose for desired task and is responsible for configuring and maintaining the Hadoop development environment. Hadoop developer job roles involves defining hadoop job flows, managing hadoop log files, developing schemas and creating hive tables, deploying HBase clusters, building new hadoop clusters , troubleshooting and debugging any runtime errors and ensuring the security of hadoop clusters.
The average salary for Hadoop developer in Bay Area is $139,000 and senior hadoop developers can earn an average of $178,000. Having a Hadoop certification will help professionals climb up the hadoop developer career path and rise quickly from distinctive specialized foundations. 2018 is the best time for professionals to get a Hadoop Certification and bag one of the highest paid big data jobs in current times.
Skillset required to become a Hadoop Developer
- Ability to write MapReduce jobs or experience in writing Pig or Hive Scripts.
- Familiarity with data loading tools such as Sqoop and Flume.
- Managing and deploying HBase.
- Knowledge of workflow schedulers like Oozie.
2) Big Data Engineer
Big data engineers job roles involves building big data solutions that have been designed by an architect. A big data engineer is responsible for developing, maintaining, testing, and evaluating big data solutions within the company. Most of the times, a big data engineer might also be involved in the design of big data solutions because of the experience they have with Hadoop based technologies such as Hive, HBase, MongoDB, Cassandra,etc. In other words, big data engineers are the products of decades of experience and rigorous training. The average starting salary for a big data engineer is $130,000 at the low end and can be as high as $190,000.
Skills Required for a Big Data Engineer
- Proficiency with Hadoop
- Well-versed with managing a Hadoop cluster and capable of solving any ongoing issues within an operational Hadoop cluster.
- Knowledge of querying tools like Pig, Hive, and Impala.
- Knowledge of messaging systems like Kafka
- Experience in integrating data from multiple sources.
- Coding expertise of some kind in either of the programming languages like –Python, SQL, R, or Scala.
3) Big Data Architect
The job role of a big data architect is synonymous to that of Solution Architects or Enterprise Architects as they are the ones who design and build efficient but cost-effective big data applications to help clients answer business questions. A big data architect must have love for data (good and bad) and has to look at a traditional data processing problems from diverse lenses. Big data architects need to be judicious about selecting the right big data tools and must be capable of embracing novel open source technologies. The average salary for a big data architect ranges from $111,750 – $184,000.
Skillset required to become a Big Data Architect
- Deep skills in open source big data tools like Hadoop and Spark.
- Knowledge of data modelling and data mining tools like Oozie, Mahout, Sqoop, Flume, and Zookeeper.
- Programming knowledge in either PHP, Python, Java or Linux.
- Understanding of data visualization tools like R Studio, Chartio, Zeppelin, and Tableau.
4) Hadoop Administrator
A hadoop administrator is responsible for administering and managing the hadoop enterprise environment. Some of the day to day activities of a Hadoop Admin include – setting up a machine in Virtual Box, formatting NameNodes, starting admin commands, backing up data and troubleshooting the hadoop cluster. The average salary for a Hadoop administrator ranges $104,000 to $156,000.
Skillset required to become a Hadoop Administrator
- Expertise in UNIX or LINUX operating system because Hadoop runs on Linux.
- Proficiency in working with hadoop cluster monitoring tools such as Ganglia or Ambari.
- A knick knack of all the components in the hadoop ecosystem.
- Excellent troubleshooting skills.
5) Big Data Analyst
A big data analyst collects, processes and perform statistically analysis of data to glean insights on the data can be used to answer important business questions and solve any challenging problems. If you have exceptional communication skills and enjoy discovering and solving data problems then this is the ideal career choice for you.
The average salary for a big data analyst ranges from $77,500 to $118,500
Skillset required to become a Big Data Analyst
- A big data analyst needs to be comfortable with one or more programming languages – Java, Python, R, SQL, Hive, Julia, and Scala.
- Should have knowledge of both relational and non-relational databases such as MySQL, DB2, Oracle, MongoDB, Cassandra, etc.
- A good understand of the computation big data frameworks such as Hadoop and Spark.
- Strong foundation of Statistics and Linear Algebra
As you can see, big data is a growing field full of potential-so don’t miss out. Big data jobs comes in all shapes and sizes with varying skillsets, it is just a matter of finding the best big data job that best matches your interests and skills. Anybody who wishes to transition completely into a big data job role must build up their resume by learning some new big data skills (like Hadoop, Spark) which will allow them to slip comfortably into the new position. Big data certification will help one leapfrog others and gain a competitive advantage. Now is the time to take up a big data course and earn a big data certification to make an exceptional career move. If you are serious about becoming an integral part of the big data community then you should also meet likeminded people who share the same career goals by attending data-focused hackathons or getting technical mentorship.