Amazon Data Engineer Customer Engagement Technology 

United States, Washington, Seattle 

45277452

As a Data Engineer on the Data and AI team, you will design and implement robust data pipelines and infrastructure that power our organization's data-driven decisions and AI capabilities. This role is critical in developing and maintaining our enterprise-scale data processing systems that handle high-volume transactions while ensuring data security, privacy compliance, and optimal performance.
Key job responsibilities
- Design and implement ETL/ELT frameworks that handle large-scale data operations, while building reusable components for data ingestion, transformation, and orchestration while ensuring data quality and reliability.- Drive the implementation of data solutions, both real-time and batch, optimizing them for both analytical workloads and AI/ML applications.
- Lead technical design reviews and provide mentorship on data engineering best practices, identifying opportunities for architectural improvements and guiding the implementation of enhanced solutions.
- Build data quality frameworks with robust monitoring systems and validation processes to ensure data accuracy and reliability throughout the data lifecycle.
- Drive continuous improvement initiatives by evaluating and implementing new technologies and methodologies that enhance data infrastructure capabilities and operational efficiency.A day in the life
The day often begins with a team stand-up to align priorities, followed by a review of data pipeline monitoring alarms to address any processing issues and ensure data quality standards are maintained across systems. Throughout the day, you'll find yourself immersed in various technical tasks, including developing and optimizing ETL/ELT processes, implementing data governance controls, and reviewing code for data processing systems. You'll work closely with software engineers, scientists, and product managers, participating in technical design discussions and sharing your expertise in data architecture and engineering best practices. Your responsibilities extend to communicating with non-technical stakeholders, explaining data-related projects and their business impact.You'll also mentor junior engineers and contribute to maintaining comprehensive technical documentation. You'll troubleshoot issues that arise in the data infrastructure, optimize the performance of data pipelines, and ensure data security and compliance with relevant regulations. Staying updated on the latest data engineering technologies and best practices is crucial, as you'll be expected to incorporate new learnings into your work. By the end of a typical day, you'll have advanced key data infrastructure initiatives, solved complex technical challenges, and improved the reliability, efficiency, and security of data systems. Whether it's implementing new data governance controls, optimizing data processing workflows, or enhancing data platforms to support new AI models, your work directly impacts the organization's ability to leverage data for critical business decisions and AI capabilities.Benefits Summary:1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan

- 3+ years of data engineering experience
- Bachelor’s degree in Computer Science, Engineering, or a related technical discipline

- Experience with AWS data services (Redshift, S3, Glue, EMR, Kinesis, Lambda, RDS) and understanding of IAM security frameworks
- Proficiency in designing and implementing logical data models that drive physical designs
- Hands-on experience working with large language models, including understanding of data infrastructure requirements for AI model training