Data Engineer I, Amazon Business Ops Analytics

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. Key job responsibilities We seek a quick-learner who can quickly familiarize themselves with a fast-paced environment, 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 strong collaborative 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 About the team Amazon Business (AB) launched in the United States in April 2015 with the vision of delivering a comprehensive procurement solution for business customers of all sizes. In the US, AB now serves Fortune 500 companies, hospital systems, local governments, and education organizations. To support AB's mission, the AB Operations team owns end to end customer experience for AB customers right from checkout to final mile delivery and sits under the broader Global Transportation Services (GTS). We are the Single Threaded WW Ops team driving B2B operations, developing products and programs unique to business customers, and enhancing the core Amazon delivery capabilities for commercial addresses. While Amazon has built its core operations over the last two decades mostly catered towards the end-consumer, we recognize that the business customers have unique needs and require a different set of features and services from their e-Commerce provider. 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 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 [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. The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status. CAN, BC, Vancouver - 80,700.00 - 134,800.00 CAD annually CAN, ON, Toronto - 80,700.00 - 134,800.00 CAD annually

Design and develop scalable data architecture, standards, and end-to-end data pipelines to support business operations. Collaborate with cross-functional teams to build data warehouse and lake platforms for ML/AI model development and implementation.

Requires at least 1 year of data engineering experience with proficiency in data modeling, warehousing, and ETL pipelines. Candidates must be skilled in query languages like SQL and scripting languages such as Python.

• Health insurance • Medical insurance • Dental insurance • Vision insurance • Prescription insurance • Basic life insurance • AD&D insurance • Registered retirement savings plan • Deferred profit sharing plan • Paid time off

• SQLPreferred
• PythonPreferred

Identified from the job description. Confirm important requirements above.

• Data engineering
• Data modeling
• Data warehousing
• ETL pipelines
• SQL
• Python
• Data architecture
• Data standards
• Data lake platforms
• Big data technologies
• Hadoop
• Hive
• Spark
• Data strategy
• Technical road map
• Data Lakes
• Informatica
• Pipelines
• Supply Chain
• Time Off Management
• Data Strategy
• Quick Learning
• Research
• Artificial Intelligence
• Software Development
• Business To Business
• Big Data
• Customer Service
• Procurement
• Data Architecture
• Data Definition Language
• Data Engineering
• Extract Transform Load (ETL)
• Data Modeling
• Data Warehousing
• Query Languages
• IBM InfoSphere DataStage
• E-Commerce Management
• Apache Hadoop
• Marketing
• Apache Hive
• Scalability
• Python (Programming Language)
• Korn Shell
• Machine Learning
• Medical Prescription
• Operations
• Palletizing
• Reengineering
• Restricted Stock

• Data & Analytics
• Technology
• Software
• Engineering
• Logistics
• Business Operations Analyst
• Data Analyst
• Statistical, Mathematical and Related Associate Professionals
• Business Intelligence Analysts
• Data Scientists

Minimum experience

2+ years

Posting language

English

Working hours

40 hours per week