Who you are
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)
Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc

What the job involves
Amazon Business (AB) is re-inventing B2B eCommerce by offering business customers of all sizes the same advantages Amazon has already brought to consumers including broad selection, low pricing, and great customer service
WW Ops Amazon Business is building the operations and supply chain solutions that will enable AB’s rapid growth by re-engineering many parts of our supply chain to offer bulk, consolidated, pallet deliveries and many other services that business customers require
As an early team member,



you will be involved in helping re-imagine what a B2B supply chain should look like and playing a key role in the technology that will power our supply chain
We seek a quick-learner who can quickly familiarize themselves with a fast-paced setting, build relationships with cross-functional teams, and assume ownership for a broad array of domains. Flexibility, and an ability to prioritize will be key. Our team culture is goal-oriented, collaborative and driven to achieve results
Design and develop the data architecture, data standards, and end to end scalable data applications and data pipelines
Build and support the data warehouse & data lake platforms for data analyses, ML/AI model development, validation and implementation
Develop robust team-oriented relationships with key partners in data engineering, software development, research, modeling and marketing teams
Develop the team's data strategy and technical road map of data storage & pipelines design and implementation

📌 Data Engineer Toronto (Canada)
🏢 Amazon
📍 Canada