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.