Aws Data Engineer

Role Overview Design, build, and optimize scalable, high-performance data platforms on AWS cloud. Play a critical role in architecting end-to-end data pipelines that support analytics and AI workloads. Drive automation, data reliability, and data quality across enterprise data platforms. Data Platform Architecture Architect modern data platforms leveraging AWS-native data services. Design data models and storage layers optimized for performance, scalability, and cost. Enable downstream consumption for business intelligence, analytics, and AI/ML use cases. Data Pipeline Development Build and maintain robust batch and streaming data pipelines using Python. Implement data ingestion, transformation, and orchestration workflows. Ensure pipelines are fault-tolerant, scalable, and maintainable. AWS Data Services Develop solutions using AWS services such as S3, Glue, Redshift, Athena, EMR, and Lambda. Optimize data processing and query performance across AWS environments. Implement secure access patterns and data governance controls. Data Quality and Automation Define and enforce data quality checks, validation rules, and monitoring frameworks. Automate data workflows and operational processes to improve reliability and efficiency. Implement logging, alerting, and observability for data pipelines. Analytics and AI Enablement Collaborate with analytics and data science teams to support reporting and AI/ML workloads. Prepare curated, high-quality datasets for advanced analytics and machine learning models. Technical Leadership Provide technical guidance and best practices for data engineering initiatives. Participate in architecture reviews and contribute to continuous improvement of data platforms.