Data Engineer, Amazon
DESCRIPTION
Core Shopping Analytics transforms disparate, raw data into actionable insights to improve customer product & program discovery and evaluation across the Amazon store. In 2025, we will own the analytics for the Homepage, Navigation, Inspire, MobileX, List, Detail Page, and cross-Store shopping experiences.
Key job responsibilities
You are a member of a 3 person DE team that owns the analytics infrastructure, standardize logging, and a central suite of fact and dim tables used by internal team members, CS business & tech partners, and Stores stakeholders across the globe. You will evolve our infrastructure to leverage latest technologies to balance accuracy and speed. You will partner with CS Tech teams to ensure new logging meets business and availability requirements. You will build and enhance central fact and dim tables to drive standardization and improve consumption by downstream consumers. Lastly, you will collaborate with DE teams across Stores to share 'best practices'.
A day in the life
We build in 5-week Sprints with 1 week for planning and 4 weeks for execution. Planning Week is used to groom the backlog and to scope & prioritize projects. We reserve the Friday of every Planning Week for a self-directed Learning Day. Over the 4 Execution Weeks, we have regular stand-ups and a mid-sprint demo. Projects will vary sprint to sprint among building derived/aggregate datasets, conducting analysis, and pushing learnings to customers.
About the team
Today, we empower ~615 Builders directly and 334 unique partner teams via our ‘Source of Truth’ datasets, self-service dashboards/gits, scheduled reports, and custom metrics consumed for cross-store evaluation. In 2024, we supported new experiences end-to-end from logging to reporting/self-service and continued maturing our foundational service offerings to enable more bandwidth for insight generation.
BASIC QUALIFICATIONS
- 1+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- 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 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 $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.