Data Engineer

Role Overview

As a Data Engineer, a typical day involves designing, developing, and maintaining comprehensive data solutions that support the generation, collection, and processing of data. This role includes creating efficient data pipelines to facilitate smooth data flow, ensuring the accuracy and quality of data throughout its lifecycle, and implementing processes to extract, transform, and load data across various systems. The position requires continuous monitoring and optimization of these data workflows to support organizational needs and enable seamless data migration and deployment.

Responsibilities

• Expected to perform independently and become an SME.
• Required active participation/contribution in team discussions.
• Contribute in providing solutions to work related problems.
• Collaborate with cross-functional teams to understand data requirements and deliver scalable data solutions.
• Monitor and troubleshoot data pipelines to ensure reliability and performance.
• Document data processes and workflows to maintain clarity and support knowledge sharing.
• Assist junior team members by providing guidance and support in their tasks.

Requirements

• Minimum 3 years of experience in Large Language Models (LLMs).
• 15 years of full-time education.
• Strong knowledge of data pipeline architecture and ETL processes.
• Experience in ensuring data quality and integrity throughout data workflows.
• Familiarity with data storage solutions and data migration techniques.
• Ability to optimize data processing for performance and scalability.

Skills

• Large Language Models (LLMs)
• AWS AI Services
• ETL
• Data Pipelines
• Data Architecture

Nice to Have

• Experience with AWS AI Services.