Data Engineer (AWS, Snowflake, PySpark, SQL) at Onsite ( Full Time )

Role Overview

We are seeking an experienced Data Engineer with strong expertise in AWS Snowflake PySpark and SQL to design develop and optimize scalable data pipelines and cloud-based data solutions. The ideal candidate will have hands-on experience building modern data platforms processing large datasets and supporting analytics and reporting requirements.

• 5 years of experience in Data Engineering.
• Strong hands-on experience with AWS Cloud Services (S3 Glue Lambda EMR Redshift etc.).
• Expertise in Snowflake Data Warehouse development and administration.
• Strong experience in PySpark/Spark for large-scale data processing.
• Advanced SQL skills with query optimization and performance tuning.
• Experience in building and maintaining ETL/ELT pipelines.
• Strong understanding of Data Warehousing and Data Lake concepts.
• Experience with data modeling partitioning and optimization techniques.
• Knowledge of version control tools such as Git.
• Experience working in Agile/Scrum environments.

• Design develop and maintain scalable ETL/ELT data pipelines.
• Build and optimize data processing solutions using PySpark and Snowflake.
• Develop cloud-native data solutions leveraging AWS services.
• Create and maintain data models for analytics and reporting requirements.
• Perform data ingestion from multiple structured and unstructured data sources.
• Optimize SQL queries data pipelines and Snowflake performance.
• Ensure data quality governance security and compliance standards.
• Collaborate with Data Architects Business Analysts and Data Scientists.
• Troubleshoot production issues and provide ongoing support.
• Implement monitoring logging and performance tuning strategies.
• Participate in code reviews and follow engineering best practices.
• Document technical solutions processes and workflows.