Amazon Data Engineer PAIR 

United States, Washington, Seattle 

63230238

Key job responsibilities
• Independently work with PAIR analysts and engineers to curate datasets for Quicksight and web-based analytical products
• Administer team-owned Redshift resources with a focus on performance, security and design
• Onboard and manage HR datasets from partner teams, working with them to gain approvals and establish the data contract.
• Track changes in team-needed dataset and manage migrations to ensure zero downtime in products.
• Create novel pipelining strategies leveraging a wide-variety of proprietary and third-party solutions in order to meet specific business needs of each delivery
• Implement and maintain security protocols for ensuring security of highly-confidential data
• Foster strong partnerships among other Data Engineering teams across PXT
• Learn and understand a growing range of Amazon and specifically PXT data resources and discover how, and when to use which data sets.
A day in the life
• Work closely with PAIR engineers, analysts and scientists in curating datasets to be used in novel people products.
• Use your skills in various DE technologies to devise strategies for pipelining datasets from a wide variety of sources.
• Measure and manage performance of a Redshift cluster with tens of users from multiple teams.
• Identify short, medium and long-term work items for yourself and the team to raise the bar on handling and security of data the team uses.

- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines

- 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 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
- • Extensive experience in data accuracy monitoring strategies.
- • Experience with Large Language Models (LLM) and agent creation.
- • Experience with one or more of the statistical modeling languages/toolboxes