- 3+ years of data engineering experience
- 3+ years of writing advanced SQL queries
- Experience with data modeling, warehousing, and building ETL pipelines
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, R, or NodeJS
- Proficiency in written and verbal communication skills including comfortability communicating and presenting to senior leadership
- Experience in designing and delivering cross-functional custom reporting solutions.
- Advanced skills in data visualization applications like Amazon QuickSight, Tableau, or similar BI tools
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, along with IAM roles and permissions
- Experience with non-relational databases / data stores such as object storage, document or key-value stores, graph databases, or column-family databases
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.
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.
World Wide Fulfillment by Amazon (FBA) empowers sellers to outsource their order fulfillment to Amazon, leveraging our world-class supply chain and technology. This allows sellers to offer customers the fastest delivery promises and the most convenient return experiences. By gaining access to Prime and non-Prime customers globally, sellers can focus on growing their business while Amazon handles fulfillment.
The WWFBA Analytics & Engineering team, part of the FBA Insights & Planning organization, is newly established to build a centralized analytics and data engineering infrastructure for WWFBA. Our mission is to deliver scalable data solutions that unify sources of truth, address data gaps, and reduce product development and operational complexity. We prioritize incremental improvements while driving towards long-term strategic goals.
We are seeking an exceptional Data Engineer who is passionate about building large-scale data pipelines and infrastructure in a dynamic big data environment. In this role, you will collaborate with software engineers, data engineers, business intelligence engineers (BIEs), and business analysts to develop robust data solutions using advanced technologies, including Spark, Ray, DBT, and various AWS tools.
Key responsibilities include:
- Leading the implementation of the WWFBA Data Lake to establish a single source of truth, supporting VP-level goals for timely and accurate business insights.
- Designing, building, and maintaining scalable, automated, and fault-tolerant data pipelines using Spark, EMR, Redshift, Glue, S3, and Python.
- Developing metrics, reports, analyses, and dashboards to drive informed business decisions.
- Simplifying complex datasets and enhancing data accessibility through innovative BI solutions.
- Collaborating cross-functionally with regional FBA, Finance, and Retail teams to ensure seamless data integration.
- Navigating ambiguous environments by applying data-driven insights and business expertise to evaluate solutions.
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