DESCRIPTION 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 Amazons Generative AI solutions and generates 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 (L5) 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. He/she is an expert with data modeling with unstructured data, ingestion pipelines and ETL design and business intelligence tools with the business to identify strategic opportunities where improvements in data infrastructure creates out-sized business impact. He/she is a self-starter, comfortable with ambiguity, able to think big (while paying careful attention to detail), mentors other engineers in team on high quality tech and enjoys 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.
Key job 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.
A day in the life
"If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!"Benefits Summary:
"Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan"
We are open to hiring candidates to work out of one of the following locations:
Austin, TX, USA | Dallas, TX, USA | Seattle, WA, USA BASIC QUALIFICATIONS - Bachelor's degree
- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience with SQL
