Big Data Engineer (Hadoop)

About This Course

Big Data Engineers (Hadoop) design, build, and manage scalable data processing systems that handle massive volumes of structured and unstructured data for analytics and business intelligence. They collaborate with data engineers, data scientists, and software teams to develop distributed data solutions that support enterprise decision-making. This course prepares learners for a career as a Big Data Engineer (Hadoop) through hands-on projects, industry workflows, collaborative learning, and real-world case studies aligned with current hiring expectations in India. Learners gain expertise in Hadoop, HDFS, MapReduce, Hive, Pig, YARN, Apache Spark, Python, SQL, ETL development, and distributed data processing. The curriculum includes practical experience with industry-standard big data ecosystems, cloud platforms, and data engineering best practices. Through live projects and capstone assignments, participants develop programming, analytical, and data engineering skills, preparing them for Big Data Engineer, Hadoop Developer, Data Engineer, Data Platform Engineer, and Analytics Engineer roles across diverse industries.

Key Responsibilities

• Design and develop scalable big data solutions using the Hadoop ecosystem
• Build and maintain ETL pipelines for processing and transforming large datasets
• Manage distributed storage and compute frameworks such as HDFS, Hive, and MapReduce
• Optimize data processing performance and ensure data quality and reliability
• Collaborate with data scientists, analysts, and engineering teams to support analytics and machine learning initiatives

Growth Path

Tools Used

Perfect For

Computer Science and Engineering Graduates | Software Developers and Backend Engineers | Data Engineering and Big Data Professionals | Cloud and Database Professionals | Machine Learning and Analytics Aspirants | Individuals Interested in Building Scalable Data Infrastructure

Fee Structure