Data Engineer I, Amazon Business Ops Analytics
- Toronto, ON, Canada
- Vancouver, BC, Canada
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Job details
- Experience
- 1+ years of data engineering experience
- Posting language
- English
- Posted
Original job description
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 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
More about this job
Responsibilities
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.
Requirements
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.
Skills
- 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
Benefits
- Health insurance
- Medical insurance
- Dental insurance
- Vision insurance
- Prescription insurance
- Basic life insurance
- AD&D insurance
- Deferred profit sharing plan
- Paid time off
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Engineering
- Logistics
Keywords
- Data Engineering
- Amazon Business
- Supply Chain
- Data Architecture
- ETL
- Data Warehouse
- Data Lake
- SQL
- Python
- Hadoop
- Hive
- Spark
- Machine Learning
- AI
- Data Strategy
- Pipelines
- B2B
- E-commerce
- Operations
- Data Modeling
- Informatica
- ODI
- SSIS
- Datastage
- Cloud Computing