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Description The Amazon ShipTech Analytics organization is looking for a smart and ambitious individual to support the development of analytical tools and data processing solutions for the Amazon transportation business. This role will work within a multi-functional BI and data engineering team with a focus on AMXL (Amazon Extra Large) and other rapidly growing delivery programs where Amazon is innovating to find new ways to deliver to our customers. The ideal candidate thrives working with large volumes of data, enjoys the challenge of highly complex technical contexts, and is passionate about data and analytics. The candidate is an expert within data modeling, ETL design and cloud/big-data technologies and passionately partners with the business to identify strategic opportunities where improvements in data infrastructure creates large-scale business impact. The candidate should be a self-starter; comfortable with ambiguity, able to think big, and enjoy working in a fast-paced and global team. It's a big ask, and we're excited to talk to those up to the challenge! Key job responsibilities · Build end-to-end data pipelines to ingest and transform data from different types of data sources and systems; from traditional ETL pipelines to event data streams · Utilize data from disparate data sources to build meaningful datasets for analytics, reporting and ML use cases · Evaluate and implement various big-data technologies and solutions (e.g. Redshift, Hive/EMR, Spark, SNS, SQS, Kinesis) to optimize processing of extremely large datasets · Understand and analyze business processes, logical data models and relational database implementations · Write high performing and optimized SQL queries · Execute research projects, and generate practical results and recommendations · Design and implement automated data processing solutions and data quality controls Basic Qualifications - Bachelor's degree - 3+ years of data engineering experience - 3+ years of SQL experience - Experience with data modeling, warehousing and building ETL pipelines - Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases) Preferred Qualifications - Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent - 5+ years of data engineering experience - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions 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. null
Most IT Jobs posts in Hyderabad ask for 3–6 years of experience (45% of 1035 that say).
From live job posts on CoreHRx, updated 5 Nov 2026. Skill figures count posts that list their skills; salary figures only posts that show a salary.
The post does not state the pay. As an estimate, comparable posts on CoreHRx advertise ₹9.5L – ₹21L a year (typical for IT Jobs in Hyderabad, 69 posts).
The post asks for 3 Yrs experience.
In Hyderabad, Bangalore.
It is a full time job.
Interview preparation · 60 questions
This guide is for Indian job seekers preparing for Java backend roles, from freshers facing campus and first-job interviews to experienced developers moving into senior positions at product companies and IT services firms. It covers what interviewers ask most in 2025 and 2026 on Java 17 and 21 and Spring Boot 3: OOP, collections, equals and hashCode, streams, exceptions, concurrency and JVM memory, then dependency injection, auto-configuration, REST controllers, validation, JPA and Hibernate, security, microservices and testing. Questions are grouped as easy, medium and hard. Read each answer, compile the code yourself and practise explaining it aloud.
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