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 up-to-date 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.

📌 Aws Data Engineer (Secunderabad)
🏢 People Prime Worldwide
📍 Secunderabad