Data Engineer

Overview Job Summary: We are looking for a skilled Data Engineer with strong hands-on experience in AWS to design, build, and maintain scalable data pipelines and cloud-based data platforms. The ideal candidate will have expertise in modern data warehousing, ETL/ELT development, and distributed data processing while ensuring data quality, performance, and security. Responsibilities Design, develop, and maintain scalable data pipelines using AWS services Build and optimize ETL/ELT workflows for structured and unstructured data Implement data lakes and data warehouses on AWS Work with large datasets to ensure high performance, reliability, and data integrity Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements Perform data modeling for analytical and operational use cases Ensure data quality, governance, and security best practices Monitor and troubleshoot data workflows and production issues Support CI/CD and automation for data platform deployments Required Skills & Experience Strong hands-on experience with AWS services such as S3, Glue, Redshift, Lambda, EMR, Athena, and RDS Proficiency in Python and SQL for data processing and analysis Experience in building and optimizing ETL/ELT pipelines Solid understanding of data warehousing and data lake architecture Experience with Apache Spark / PySpark Knowledge of workflow orchestration tools (Airflow or similar) Familiarity with streaming frameworks (Kinesis/Kafka) is a plus Experience with data modeling and performance tuning Understanding of DevOps, CI/CD, and infrastructure as code (Terraform/CloudFormation) Experience working in Agile/Scrum environments Good to Have Experience with Snowflake on AWS Exposure to real-time data processing AWS certification (e.g., AWS Certified Data Analytics / Solutions Architect) Soft Skills Strong problem-solving and analytical skills Excellent communication and stakeholder management Ability to work in a fast-paced, collaborative environment #J-18808-Ljbffr