Data Engineer

Design, develop, and maintain ETL pipelines involving large-scale data . Develop data processing and analytics applications primarily using PySpark and Python . Build scalable and distributed data processing solutions using Apache Spark . Develop and deploy data applications on AWS cloud . Work with AWS services related to storage, compute, ETL, data warehousing, analytics, and streaming . Implement distributed storage and processing solutions capable of handling high-volume datasets. Design data processing applications with a focus on performance, scalability, reliability, and optimization . Work with both SQL and NoSQL databases for data storage, processing, and analytics. Write, optimize, and analyze SQL, HQL, and NoSQL queries . Troubleshoot data pipeline and processing issues and ensure data quality and reliability. Collaborate with data engineers, analysts, architects, and other technical teams to deliver data-driven solutions. Skills:- ELT, SQL, PySpark, Amazon Web Services (AWS) and NOSQL Databases