Big Data Engineer

A big data engineer is a specialist who develops and oversees an organization's big data infrastructure and applications, ensuring swift analysis and results from large datasets.

The role of big data engineers involves building upon the frameworks created by data architects. They are responsible for creating, maintaining, testing, and evaluating big data solutions, often using Hadoop-based technologies like MapReduce, Cassandra, Hive, and MongoDB.

Responsibilities of a Big Data Engineer

Big data engineers are designing the architecture of a big data platform, maintaining data pipelines, organizing data, customizing and managing necessary data tools and analytics systems, and establishing data access for data scientists.

Their main responsibilities fall into two categories:

Performance optimization

This involves enhancing the infrastructure and tools to accelerate data queries. Key activities include improving database query methods and ensuring data is ingested efficiently. They work on data partitioning, separating datasets into distinct partitions for better management and quicker access. Additionally, they focus on database indexing to facilitate faster searches in large datasets. Efficient data ingestion involves identifying patterns within vast datasets using different data mining techniques and APIs.

Stream processing

Stream processing is the real-time processing of continuous data streams. Big data engineers design streaming data architectures that automatically gather, distribute, and process data in real-time, ensuring orderly execution. They also develop and manage systems that can handle the simultaneous processing of multiple data streams, ensuring these systems can scale effectively and maintain functionality even when issues arise.