Data Engineer , Global Procurement Technology

- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience working on and delivering end to end projects independently
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience with SQL
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
- Knowledge of distributed systems as it pertains to data storage and computing
- Knowledge of batch and streaming data architectures like Kafka, Kinesis, Flink, Storm, Beam

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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.
Amazon's Global Procurement Organization manages indirect supply chain for World Wide Operations and Delivery Services. We work with massive amounts of data and leverage them for advanced analytics and applications.

If you want to work with data at a very large scale, and you want to collaborate closely with Data Scientists, and Software Teams to build solutions simplifying the complexity of Amazon supply chain, you belong here with us!

We are seeking a Data Engineer who is customer focused, relentless and driven to help us build out a new initiatives. You will collaborate closely with product managers, developers, data scientists and leaders across the org. To be successful in this role, you should have broad skills in database design, be comfortable dealing with large and complex data sets, modeling and designing a strong data warehouse and building self-service data platforms for stakeholders to utilize the data we manage.