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Hyderabad · On-site · 2-5 Yrs · 5 days ago
Internet & Web Services · 10000+ Employees · Seattle, US
All Amazon teams and businesses, from Prime delivery to AWS, are guided by four key tenets: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. We are driven by the excitement of building technologies, inventing products, and providing services that transform the way our customers live their lives and run their businesses.
Hiring: Engineering
What employees say
+ Good compensation, Challenging work, Great tech stack
− Work life balance, middle management, Pushing AI down SDE's throat, not transparent management
More reviews on the company profile.
Interview experience · Application Engineer
4 to 5 Rounds, Initial phone screening will be done over phone. Then followed by 2 technical rounds, which have tech questions and coding problems to solve. some times bar raiser round. Then HM round followed by HR round
Difficult difficulty · India · 10,943 reports
More interview insightsJob description
Overview
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.
Responsibilities
- 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.
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
- 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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Job application FAQ
Last updated 27 October 2026
- How do I apply for Data Engineer, WW Returns & ReComm Tech& Inn at Amazon?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Amazon may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this Data Engineer, WW Returns & ReComm Tech& Inn role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is Data Engineer, WW Returns & ReComm Tech& Inn remote or on-site in Hyderabad, Telangana?
- This listing is marked on_site with location Hyderabad, Telangana. Confirm details on the job description before applying.
- What skills matter for this Data Engineer, WW Returns & ReComm Tech& Inn role at Amazon?
- This is a mid-level Data Engineer, WW Returns & ReComm Tech& Inn role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.