Data Engineer - PySpark

Description : Role : Data Engineer (AWS | PySpark) Experience : 4 - 6 Years Location : Chandigarh Work Mode : Work from Office / Hybrid Role Overview : We are looking for a Data Engineer with 4 - 6 years of experience in building and optimizing data pipelines and cloud-based data platforms. You will work on scalable data solutions, supporting analytics, reporting, and business intelligence for a US-based product company in the financial domain. Key Responsibilities : - Develop and maintain ETL / ELT data pipelines - Work with AWS services (especially AWS Glue, S3) for data ingestion and processing - Build PySpark / Spark SQL pipelines for large-scale data processing - Perform data transformation, validation, and optimization - Work with Databricks (preferred) for data engineering workflows - Write and optimize complex SQL queries - Support data warehousing and reporting use cases - Collaborate with cross-functional teams (Product, Analytics, Engineering) - Troubleshoot data pipeline issues and ensure data quality Required Skills : - Strong experience in Python / PySpark - Good knowledge of SQL (advanced queries, joins, optimization) - Hands-on experience with AWS (Glue, S3, basic services) - Experience in ETL / ELT pipeline development - Understanding of data warehousing concepts - Exposure to Databricks (preferred) - Basic understanding of data governance and data quality Preferred Skills : - Experience in financial domain / fintech products - Exposure to Tableau / Power BI - Knowledge of Spark SQL and Delta Tables - Understanding of batch and real-time data processing Benefits : - Competitive compensation - Opportunity to work on AI-powered data platforms - Exposure to US-based clients and modern tech stack - Strong learning and career growth opportunities - Collaborative and product-driven environment (ref:hirist.tech) Description : Role : Data Engineer (AWS | PySpark) Experience : 4 - 6 Years Location : Chandigarh Work Mode : Work from Office / Hybrid Role Overview : We are looking for a Data Engineer with 4 - 6 years of experience in building and optimizing data pipelines and cloud-based data platforms. You will work on scalable data solutions, supporting analytics, reporting, and business intelligence for a US-based product company in the financial domain. Key Responsibilities : - Develop and maintain ETL / ELT data pipelines - Work with AWS services (especially AWS Glue, S3) for data ingestion and processing - Build PySpark / Spark SQL pipelines for large-scale data processing - Perform data transformation, validation, and optimization - Work with Databricks (preferred) for data engineering workflows - Write and optimize complex SQL queries - Support data warehousing and reporting use cases - Collaborate with cross-functional teams (Product, Analytics, Engineering) - Troubleshoot data pipeline issues and ensure data quality Required Skills : - Strong experience in Python / PySpark - Good knowledge of SQL (advanced queries, joins, optimization) - Hands-on experience with AWS (Glue, S3, basic services) - Experience in ETL / ELT pipeline development - Understanding of data warehousing concepts - Exposure to Databricks (preferred) - Basic understanding of data governance and data quality Preferred Skills : - Experience in financial domain / fintech products - Exposure to Tableau / Power BI - Knowledge of Spark SQL and Delta Tables - Understanding of batch and real-time data processing Benefits : - Competitive compensation - Opportunity to work on AI-powered data platforms - Exposure to US-based clients and modern tech stack - Strong learning and career growth opportunities - Collaborative and product-driven environment (ref:hirist.tech)