• Primary skills:Technology->Big Data - Data Processing->PySpark

Key Responsibilities

• Design, develop, and maintain scalable batch data pipelines using PySpark and Apache Spark for large datasets.
• Perform data ingestion, transformation, and enrichment while ensuring accuracy, completeness, and consistency of outputs.
• Optimize Spark jobs for performance (partitioning, caching, joins, shuffles) and improve runtime efficiency and resource utilization.
• Implement robust error handling, logging, and monitoring to ensure reliable pipeline execution and faster issue resolution.
• Collaborate with cross-functional teams to gather requirements, define data contracts, and deliver well-documented solutions.
• Conduct code reviews, follow engineering best practices, and contribute to reusable components and standards.
• Troubleshoot production issues, perform root-cause analysis, and drive corrective and preventive actions. Minimum Qualifications:
• Bachelor’s degree (or equivalent) in Engineering/Computer Science/IT or related field.




• 3–5 years of experience in data engineering or big data development roles.
• Strong hands-on experience with PySpark and Apache Spark for building data processing workflows.
• Solid understanding of distributed data processing concepts and performance tuning fundamentals.
• Ability to translate business requirements into technical implementations and deliver within timelines. Preferred Qualifications:
• Experience building end-to-end Spark applications including job orchestration, dependency management, and production support readiness.
• Strong data transformation skills with a focus on data quality checks, reconciliation, and pipeline reliability.
• Exposure to designing modular, reusable Spark components and maintaining clean, maintainable codebases.
• Familiarity with structured and semi-structured data formats and productive processing patterns in Spark.
• Proven ability to collaborate effectively across teams, communicate clearly,

📌 Pyspark (Bengaluru)
🏢 Infosys
📍 Bengaluru