Big Data Architecture:
Design, build, and implement scalable Big Data solutions to process and analyze vast datasets in a timely and efficient manner.
Data Pipeline Development:
Develop ETL (Extract, Transform, Load) pipelines for large-scale data processing. Ensure data pipelines are automated, scalable, and robust to handle high volumes of data.
Distributed Systems:
Work with distributed computing frameworks (e.g., Apache Hadoop, Apache Spark, Flink) to process big datasets across multiple systems and clusters.
Data Integration:
Integrate data from multiple sources (structured, semi-structured, and unstructured) into a unified data architecture.
