Role Overview : We are looking for strong Data Engineering professionals with hands-on expertise in PySpark, AWS and SQL to build, optimize and support scalable ETL/ELT pipelines and cloud-based data solutions. Candidates should be comfortable working with large datasets, performance tuning and end-to-end data pipeline development.Key Skills : PySpark, AWS, SQL, Data Engineering, ETL/ELT, Data PipelinesKey Responsibilities : - Design, develop and maintain scalable data pipelines and ETL/ELT workflows using PySpark and SQL.- Build and support AWS-based data engineering solutions using relevant services such as S3, Glue, EMR, Redshift, Lambda or similar services.- Perform data extraction, transformation, ingestion and integration across structured and semi-structured data sources.- Write and optimize complex SQL queries for data transformation, validation, reconciliation and performance.- Process large datasets using Spark/PySpark and apply partitioning, caching and performance-tuning techniques where required.- Monitor production pipelines, troubleshoot failures and resolve data-quality and performance issues.- Collaborate with architects,



analysts and engineering teams to translate requirements into reliable data solutions.- Follow coding, testing, deployment, documentation and data-governance best practices.Required Experience : - 5 - 10 years of overall experience in Data Engineering / ETL development.- Strong hands-on development experience in PySpark and Apache Spark concepts.- Strong SQL skills, including joins, CTEs, window functions, query optimization and data validation.- Hands-on experience with AWS cloud data services and cloud-based data pipelines.- Positive understanding of data warehousing, dimensional concepts, ETL/ELT and batch/large-scale data processing.- Ability to independently troubleshoot pipeline, data and performance issues.Preferred : - Experience with AWS Glue, EMR, S3, Redshift, Lambda, Step Functions or comparable AWS data services.- Experience with Airflow or other workflow orchestration tools, CI/CD and Git-based development practices.- Immediate or short-notice availability is strongly preferred. (ref:hirist.tech)

📌 EY - Data Engineer - PySpark/AWS (Pune)
🏢 Ernst & Young LLP - India
📍 Pune