Engineers who design and develop big data pipelines, collect data from different sources and organize it into sets for analysts and data scientists to work with.
Data expansion and accelerated processing have led to problems. Data volume, speed, inconsistencies, and different data formats are all factors that have pushed demand for big data engineers upward.
1. Design big data engineer architecture platform. 2. Improve performance by monitoring infrastructure. 3. Maintain data pipeline. 4. Manage integration tools, databases, warehouses, and analytical systems.
1. Data Architect 2. BI Architect 3. Senior Big Data Engineer
1. Obtain relevant degree 2. Learn DSA, SQL, etc. 3. Proficiency in programming languages (Python, Java Scala, etc.) 4. Big Data tools (Apache Hadoop, Spark and Kafka) 5. Learn distributed Systems
1. Hadoop v2, MapReduce, and HDFS. 2. Working of Spark NoSQL databases like HBase, MongoDB, etc. 3. ETL frameworks 4. Messaging systems, like Kafka 5. Big Data ML toolkits like Mahout, SparkML, etc.
Big Data engineers earn an average salary of ₹7,22,000/yr. However, it may differ based on various factors, such as experience, location, employer, and skills.
How to create an effective Big Data Engineer Resume?