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职位：Analytics Engineering Intern (Summer 2024)
Curious and motivated learner - enrolled and working towards a Master’s level degree in Data Science, Economics, Statistics, Computer Science, Engineering, Mathematics, or a related analytics field - graduating in December 2024/ Summer 2025 or later
Clear communicator - you are concise and articulate in speech and writing
Able to manipulate and evaluate data with SQL to surface actionable insights
Experience with data analysis and analytics tools such as Tableau, PowerBI, Qlik, Looker, etc.
Practical knowledge of a scripting language such as Python or R for analytics or visualization
Coursework or some experience with data preparation (ETL) pipelines, data structures and data modeling, data warehouse architecture
职位：Internship, Business Analyst, North America Used Cars (Winter/Spring 2024)
行业分类：Automotive,Artificial intelligence,Renewable energy
公司规模：127,855人
工作地点：Fremont, California
职位要求：
Conduct routine analysis and reporting on areas to improve the business performance.
Support managers in building business cases for initiatives they are driving for the business
Participate in project definition, scoping, and evaluation of multiple high-profile projects
Implement systems and process optimization projects in accordance with the operating plan
Prioritize multiple projects and milestones, while adhering to business-critical deadlines
Communicate progress and status in diverse forums, including executive leadership
Understand and convey business issues and technical concepts
Perform ad hoc data analysis and deck preparation for executive reviews
Find new opportunities to reveal data insight with your keen business senses
【Amazon】
职位：Data Engineer, Sponsored TV ads, Gaming and OTT Ads
BASIC QUALIFICATIONS
3+ years of data engineering experience
Experience with data modeling, warehousing and building ETL pipelines
PREFERRED QUALIFICATIONS
Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
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