Python+Spark Scala

Responsibilities :

Big Data & Spark Development Develop and maintain data processing pipelines using Apache Spark (PySpark & Scala) Work with Spark DataFrames, RDDs, and Spark SQL Implement transformations, joins, aggregations, and optimizations Tune Spark jobs for performance, scalability, and reliability Python & Scala Programming Write clean, efficient, and scalable code in Python and Scala Develop modular and reusable components Integrate data pipelines with various applications and APIs ETL & Data Engineering Design and build ETL workflows for structured and unstructured data Extract data from multiple sources (databases, APIs, flat files) Perform data cleansing, transformation, and validation Ensure data accuracy, consistency, and completeness Data Platforms & Integration Work with Hadoop ecosystem (HDFS, Hive, Spark) Handle large datasets in data lakes and warehouses Process data in formats like Parquet, ORC, JSON, CSV Collaboration & Support Work with data engineers, analysts, and business stakeholders Troubleshoot pipeline issues and provide production support Participate in Agile/Scrum processes Maintain technical documentation

Additional Responsibilities:

Core Skills 2â€5 years of experience in Python development Hands-on experience with Apache Spark (PySpark and/or Scala) Strong understanding of data processing and ETL concepts Good knowledge of SQL and relational databases

Technical and Professional Requirements:

Primary skills:Technology- Big Data - Data Processing- Spark,Technology- Java- Apache,Technology- Machine Learning- Python