Big Data is one of the leading tech trends that is benefiting businesses by allowing them to understand their customers better, effective fraud and anomaly detection, improving efficiency, cost optimization, and subsequently leading to an effective decision-making process. The demand for Big Data professionals is almost in every sector whether it be IT, finance, manufacturing, retail, etc. Other than that, there are various job roles that fall under the Big Data domain like Big Data Engineer, BigData Architect, etc. Hence, if you’re considering making a career in Big Data, you can surely go for it.
What is Big Data?
Big Data is concerned with the collection of huge data associated with characteristics like large variety, more velocity along with increased volume simply known as 3 Vs. There are primarily 3 types of Big Data – Structured data, Unstructured data, and Semi-structured data. This voluminous structured, semi-structured, or unstructured data is processed to gather useful insights for subsequently making effective business decisions, etc.
Is Big Data in Demand?
According to numerous research, it has been found that data science-related jobs have a very high demand and will grow by 31 percent in the next few years. Many top companies are always in need of professionals who have knowledge of data science along with a proper skill set. Also, these highly demanding jobs have good pay for those with the right expertise.
Highest Paying Big Data Jobs :
This blog represents a high-level view of career opportunities that are existing in the Big Data Domain and basic skill requirements. Some of the designations and responsibilities are mentioned here.
Role – Data Scientist
- The big data scientist needs to be familiarized with some of the languages among Python, R programming, Java, Ruby, Clojure, Matlab, Pig, and SQL.
- They need to understand Hadoop, Hive, and MapReduce.
- In addition need to be familiar with disciplines such as:
- Natural Language Processing: the interactions between computers and humans;
- Machine learning: using computers to improve as well as develop algorithms;
- Conceptual modeling: to be able to share and articulate modeling;
- Statistical analysis: to understand and work around possible limitations in models;
- Predictive modeling: most of the big data problems are towards being able to predict future outcomes
Role – Big Data Engineer / BigData Developer / BigData Architect
- Step by step approach for a software Engineer who is expert in Java / C / C++ => HADOOP (APIs, MR Coding, Ecosystem & Admin ) => HIVE/PIG/IMPALA/ML => OOZIE Plus Monitoring.
- Architect, Design & Develop BigData based software from scratch / Upgrade / Maintain.
- Step by step approach for a software Engineer who is expert in ORACLE / PL/SQL/ MS SQL / TERRADATA / DATA WAREHOUSING => HADOOP (APIs, MR Coding, Ecosystem & Admin ) => HIVE/PIG/IMPALA/ML => OOZIE Plus Monitoring tools.
- Architect, Design & Develop BigData-based data warehouse
Role – Big Data DBA
- Design and Development of Data modeling.
- Hadoop ecosystem installation and configuration.
- DR / Cluster to Clysters – Database backup and recovery.
- Database connectivity and security.
- Performance monitoring and tuning; Configuration based
- Disk space management.
- Software patches and upgrades for Unix as well as Hadoop
Role – Big Data Admin/Hadoop Administrator
- Good Linux and shell Scripting background
- Good knowledge of the Hadoop Ecosystem and technologies.
- Understanding of Hadoop design principles and factors that affect distributed system performance, including hardware and network considerations.
- Experience in providing Infrastructure Recommendations, Capacity Planning, and developing utilities to monitor clusters better
- Experience in managing large clusters with huge volumes of data
- Experience with cluster maintenance tasks such as the creation and removal of nodes, cluster monitoring, and troubleshooting. Manage and review Hadoop log files.
- Experience installing and implementing security for Hadoop clusters.
Role : BigData – Hadoop operations / Production Support / Operations
- Good Linux and shell Scripting background
- Good knowledge of the Hadoop Ecosystem and technologies.
- Cluster maintenance
- Job Management / Job failures / Investigation / Restart
- Autosys / Oozie integration data analysis – Data recovery
- Cluster to Cluster data movement
- Escalations
- Operations management.