Data Engineer, OCEANS

Do you love data? Do you want to learn new technologies? Join our OCEANS team and help shape the future of employee compensation at Amazon! Our job is to establish data definitions, conduct research, and launch products to support the Amazon Leadership Team and Consultants in making pay decisions for employees.

As a Data Engineer on our team, you'll work with cutting-edge technologies and complex data environments. You'll be responsible for enhancing our existing data architecture to further standardize metrics and definitions, developing end-to-end data engineering solutions for complex analytical problems, and collaborating with analysts, data scientists, and software engineers to translate data into actionable insights.

This role requires you to live at the intersection of data, software, and science. We leverage a comprehensive suite of AWS technologies, with key tools including S3, Redshift, DynamoDB, Lambda, API's, Glue, MWAA, DataZone, and SageMaker. You will drive the development process from design to release.

Key job responsibilities

Managing data ingestion from heterogeneous data sources, with automated data quality checks.
Creating scalable data models for effective data processing, storage, retrieval, and archiving.
Using scripting for automation and tool development, which is scalable, reusable, and maintainable.
Providing infrastructure for compensation analytics and science use cases.
Using industry best practices in building CI/CD pipelines.


About the team
Join our team at Amazon, where data drives our global compensation strategy. As a business intelligence and analytics unit, we're shaping how Amazon compensates million+ employees worldwide. Our mission: to leverage advanced analytics in evaluating and scaling our annual pay policy, directly influencing the company's growth trajectory. If you're seeking a role with large-scale impact, we offer the opportunity to apply your analytical skills at the intersection of big data, human resources, and business strategy. Your work will revolutionize Amazon's compensation landscape, ensuring fair, competitive, and forward-thinking pay practices that support our company's continued success and expansion.

Basic Qualifications

- 1+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, KornShell)

Preferred Qualifications

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.

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 $91,200/year in our lowest geographic market up to $185,000/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.