PySpark Developer

Key Responsibilities Design, develop, and maintain scalable data pipelines using PySpark. Develop ETL/ELT processes for data ingestion, transformation, and loading. Work with large datasets in distributed computing environments. Optimize Spark jobs for performance, scalability, and reliability. Develop data processing solutions using Spark SQL, DataFrames, and RDDs. Integrate data from multiple sources, including databases, APIs, and cloud environments. Collaborate with data engineers, architects, and business stakeholders. Perform troubleshooting and root cause analysis for production issues. Ensure data quality, governance, and security standards are followed.

A day in the life of an Infoscion

• As part of the Infosys delivery team, your primary role would be to interface with the client for quality assurance, issue resolution and ensuring high customer satisfaction.
• You will understand requirements, create and review designs, validate the architecture and ensure high levels of service offerings to clients in the technology domain.
• You will participate in project estimation, provide inputs for solution delivery, conduct technical risk planning, perform code reviews and unit test plan reviews.
• You will lead and guide your teams towards developing optimized high quality code deliverables, continual knowledge management and adherence to the organizational guidelines and processes.
• You would be a key contributor to building efficient programs/ systems and if you think you fit right in to help our clients navigate their next in their digital transformation journey, this is the place for you! If you think you fit right in to help our clients navigate their next in their digital transformation journey, this is the place for you! Required Skills 5-9 years of experience in Data Engineering or Big Data Development. Strong hands-on experience with PySpark and Python. Experience with Apache Spark, Spark SQL, DataFrames, and ETL development. Good knowledge of Hadoop Ecosystem (Hive, HDFS, YARN). Strong SQL and database skills. Experience with Unix/Linux environments. Knowledge of data warehousing concepts.