Data Engineer Gen AI, Customer Engagement Technology

Amazon.com • Seattle, WA

70d • $118,900 - $205,600

About The Position

Are you passionate about data, code, and Generative AI? Does the prospect of dealing with massive volumes of large language model data excite you? Do you want to build data engineering solutions that process billions of interactions with Amazon's Generative AI solutions and generate insights from those interactions? Do you want to use Large Language Models (LLMs) to help to improve the customer service experience? Do you want to create a next-generation data storage product for large language models? If so, then Customer Service's Customer Engagement Technology Team is for you! We are seeking a Data Engineer to join the Customer Engagement Technology Team (CET) focused on Self-Service Automation. As a Data Engineer you will be responsible for designing and building our data storage platforms for LLMs. The ideal candidate relishes working with large volumes of data, enjoys the challenge of highly complex technical contexts, and, above all else, is passionate about data and analytics. They are an expert with data modeling with unstructured data, ingestion pipelines and ETL design and business intelligence tools working with the business to identify strategic opportunities where improvements in data infrastructure create out-sized business impact. They are a self-starter, comfortable with ambiguity, able to think big (while paying careful attention to detail), mentor other engineers in the team on high quality tech, and enjoy working in a fast-paced team. We're excited to talk to those up to the challenge! The mission of the CET team within Customer Service is to create Earth's best customer service solutions through empowering our customers to utilize automation to resolve their issues quickly and efficiently. You will be a key component of our leadership team and will influence our science and engineering roadmap to harness the power of LLMs to solve customer problems.

Requirements

• 3+ years of data engineering experience.
• Experience with data modeling, warehousing and building ETL pipelines.
• Knowledge of batch and streaming data architectures like Kafka, Kinesis, Flink, Storm, Beam.
• Experience in scripting for automation (e.g. Python) and advanced SQL skills.

Nice To Haves

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions.
• Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases).
• Knowledge of distributed systems as it pertains to data storage and computing.
• Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence.

Responsibilities

• Design, develop and maintain product data pipelines, meeting data and privacy standards.
• Develop robust and scalable data and insight platforms using SQL and Spark.
• Support analytical research and provide recommendations to business challenges.
• Continually improve the data quality and operations, via automation and building full CI/CD data pipelines.
• Develop and influence the teams' data strategy and data storage roadmap through working closely with business stakeholders.

Benefits

• Medical, Dental, and Vision Coverage
• Maternity and Parental Leave Options
• Paid Time Off (PTO)
• 401(k) Plan

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: General Merchandise Retailers
• Number of Employees: 5,001-10,000 employees