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Description

The Learning & Development Science team in Amazon Logistics (AMZL) builds state-of-the-art Artificial Intelligence (AI) solutions for enhancing leadership and associate development within the organization. We develop technology and mechanisms for measuring the impact of learning programs, improving the training content and recommending the personalized learning courses based on the post-training performance curves for different learner profiles.

Key job responsibilities

- Design, develop, and maintain scalable data pipelines to support Analytic/ ML model development and production deployment.

- Implement and maintain CI/CD pipelines for the data, analytics, and ML solutions.

- Collaborate with fellow data engineers, business intelligence engineers, applied/data scientists, and other team members to understand data requirements, translate them into technical requirements, and implement efficient data processing solutions.

- Create and manage data warehouses and data lakes, ensuring proper data governance and security measures are in place.

- Implement best practices in data system creation, data integrity, and documentation

- Stay current with emerging technologies and best practices in data engineering, and propose innovative solutions to improve data infrastructure and processes for ML models and analytics applications.

- Participate in code reviews and contribute to the development of best practices for data engineering within the team.

Basic Qualifications

- 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 in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS

- Experience working with Git or an equivalent distributed version control system

Preferred Qualifications

- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

- Experience providing technical leadership and mentoring other engineers for best practices on data engineering

- Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent

- Experience with Infrastructure as Code (IaC) by tools such as CDK.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,900/year in our lowest geographic market up to $205,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.