Data Engineer , Data & AI, Customer Engagement Technology

Description

As a Data Engineer on the Data and AI team, you will 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.

You'll be part of a dynamic team that designs and implements comprehensive data solutions, from real-time processing architectures to secure storage solutions and privacy-compliant data access layers. The role involves close collaboration with cross-functional teams, including software development engineers, product managers, and scientists, to create data products that power critical business capabilities. You'll have the opportunity to work with leading technologies in cloud computing, big data processing, and machine learning infrastructure, while contributing to the development of robust data governance frameworks.

If you're passionate about solving complex technical challenges in high-scale environments, thrive in a collaborative team setting, and want to make a lasting impact on our organization's data infrastructure, this role offers an exciting opportunity to shape the future of our data and AI capabilities.

Key job responsibilities

• Collaborate with experienced cross-disciplinary Amazonians to conceive, design, and bring innovative ideas to market.
• Contribute to the implementation and maintenance of data architecture, infrastructure and storage solutions under the guidance of senior engineers, focusing on data quality and reliability.
• Assist in building data pipelines, pipeline orchestration, data governance framework, data quality testing and pipeline management using continuous integration and deployments while learning best practices from experienced team members.
• Participate in technical discussions and contribute to database design decisions, learning about scalability and reliability considerations while implementing optimized code according to team standards.
• Execute assigned technical tasks within larger projects, writing well-tested ETL/ELT pipelines, providing thorough documentation, and following established data engineering practices.
• Work in an agile environment to deliver high-quality data pipelines supporting real-time and end of day data requirements.
  
  

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 troubleshooting, data quality deep dives, developing optimized ETL/ELT processes, implementing data governance controls, unit testing code and gets it reviewed. You’ll continually improve ongoing processes, automating or simplifying data engineering efforts. You'll work closely with senior engineers, data scientists, and product managers, participating in technical design discussions and learn the business context and technologies in data architecture. Your responsibilities extend to communicating with non-technical stakeholders, explaining root cause and their business impact. 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 continually. By the end of a typical day, you'll have advanced key data infrastructure initiatives, solved 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

About The Team

The Data and Artificial Intelligence (AI) team is a new function within Customer Engagement Technology. We own the end-to-end process of defining, building, implementing, and monitoring a comprehensive data strategy. We also develop and apply Generative Artificial Intelligence (GenAI), Machine Learning (ML), Ontology, and Natural Language Processing (NLP) to customer and associate experiences.

Basic Qualifications

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

Preferred Qualifications

• 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
  
  

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.


Company - ADCI HYD 13 SEZ

Job ID: A2996963