AWS SENIOR DATA ENGINEER

Role Overview: As an AWS Senior Data Engineer, you will be responsible for designing and maintaining scalable ETL pipelines using AWS Glue, PySpark & Python. You will build and manage workflows with AWS services such as Glue, Lambda, S3, Athena, DynamoDB, and Step Functions. Your role will involve writing and optimizing SQL queries for complex data transformations, implementing Infrastructure as Code (IaC) using Terraform, and ensuring data quality, performance, and reliability at scale. Collaboration with cross-functional teams, troubleshooting, optimization of pipelines, and maintaining clear documentation are key aspects of this role. Key Responsibilities: - Design and maintain scalable ETL pipelines using AWS Glue, PySpark & Python. - Build & manage workflows with AWS services: Glue, Lambda, S3, Athena, DynamoDB, Step Functions. - Write and optimize SQL queries for complex data transformations. - Implement Infrastructure as Code (IaC) using Terraform. - Ensure data quality, performance, and reliability at scale. - Collaborate with cross-functional teams (Data Engineers, Analysts, Architects). - Troubleshoot and optimize pipelines for efficiency. - Maintain clear documentation and continuously improve data workflows. Qualifications Required: - Strong proficiency in Python & PySpark for large-scale data processing. - Solid experience with AWS Data Engineering services (Glue, S3, Lambda, Athena, DynamoDB, Step Functions). - Advanced SQL development and query optimization skills. - Hands-on experience with Terraform for AWS infrastructure automation. - Expertise in designing cloud-based data architectures. Additional Details: The ideal candidate for this role should also have exposure to Snowflake for data warehousing and experience with DBT for data modeling & transformation. Strong collaboration, communication, and version control skills (Git) are considered nice to have for this position.,