Data Engineer, WW Returns & ReComm Tech& Inn

The Data Engineer will own the data infrastructure for the Reverse Logistics Team which includes collaboration with software development teams to build the data infrastructure and maintain a highly scalable, reliable and efficient data system to support the fast growing business. You will work with analytic tools, can write excellent SQL scripts, optimize performance of SQL queries and can partner with internal customers to answer key business questions. We look for candidates who are self-motivated, flexible, hardworking and who like to have fun.

About the team
Reverse Logistics team at Amazon Hyderabad Development Center is an agile team whose charter is to deliver the next generation of Reverse Logistics platform. As a member of this team, your mission will be to design, develop, document and support massively scalable, distributed data warehousing, querying and reporting system.

Basic qualifications

- 2+ 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)
- Knowledge of AWS Infrastructure
- Knowledge of writing and optimizing SQL queries in a business environment with large-scale, complex datasets
- Strong analytical and problem solving skills. Curious, self-motivated & a self-starter with a ‘can do attitude’. Comfortable working in fast paced dynamic environment

Preferred qualifications

- Bachelor's degree in a quantitative/technical field such as computer science, engineering, statistics
- Proven track record of strong interpersonal and communication (verbal and written) skills.
- Experience developing insights across various areas of customer-related data: financial, product, and marketing
- Proven problem solving skills, attention to detail, and exceptional organizational skills
- Ability to deal with ambiguity and competing objectives in a fast paced environment
- Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing and operations

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