Job Description

Responsibilities :

Key Responsibilities Design and develop scalable data pipelines using PySpark and Apache Spark. Build and optimize ETL/ELT frameworks for processing large volumes of structured and unstructured data. Develop high-performance Spark applications using Spark SQL, DataFrames, and RDDs. Work closely with data architects and business teams to define data requirements. Implement data quality, validation, and governance processes. Optimize Spark jobs for performance, memory management, and scalability. Integrate data from various sources including databases, APIs, cloud storage, and streaming platforms. Support production deployments and resolve performance bottlenecks. Mentor junior developers and participate in code reviews.

Technical and Professional Requirements:

Mandatory Skills 8+ years of IT experience. Strong hands-on experience in PySpark and Python. Expertise in Apache Spark, Spark SQL, DataFrames, and ETL Development. Strong SQL and database concepts. Experience with Hadoop Ecosystem (Hive, HDFS, YARN). Experience in Data Warehousing and Data Modeling. Hands-on experience with Unix/Linux.