Data Engineer I, Intl. Seller Growth
Amazon
2 - 5 years
Hyderabad
Posted: 01/05/2025
Job Description
Come and be part of the International Seller Services (ISS) Central Analytics Data Engineering (DE) team and work on solving problems!
We are a team of DEs who support Applied Scientists, Data Scientist, and Economists who experiment, research, and turn machine/deep learning and AI research into great products for our customers.
ISS is seeking a smart, highly
- motivated, and experienced Data Engineer to join our team.
In this role, you'll help us create the right Data and ML infrastructure.
As a Data Engineer, you will provide technical leadership, lead data engineering initiatives and build end
- to
- end analytical solutions that are highly available, scalable, stable, secure, and cost
- effective.
You are passionate about working with huge datasets and have experience with the organization and curation of data for analytics.
You have a strategic and long term view on architecting advanced data eco systems.
You are experienced in building efficient and scalable data services and have the ability to integrate data systems with AWS tools and services to support a variety of customer use cases/applications.
Key job responsibilities
As a Data Engineer, you will provide technical leadership, lead data engineering initiatives and build end
- to
- end analytical solutions that are highly available, scalable, stable, secure, and cost
- effective.
You are passionate about working with huge datasets and have experience with the organization and curation of data for analytics.
You have a strategic and long term view on architecting advanced data eco systems.
You are experienced in building efficient and scalable data services and have the ability to integrate data systems with AWS tools and services to support a variety of customer use cases/applications.
Design, implement and operate large
- scale, high
- volume, high
- performance data structures for analytics and data science.
Implement data ingestion routines using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools.
Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.
Collaborate with engineers to help adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation
Identify opportunities in existing data solutions for improvements
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)
- Knowledge of writing and optimizing SQL queries in a business environment with large
- scale, complex datasets
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.
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.
About Company
Amazon is a multinational technology and e-commerce company founded by Jeff Bezos in 1994. Initially focused on selling books online, it quickly expanded into a broad range of products and services, including electronics, cloud computing (via Amazon Web Services), streaming, and artificial intelligence. Amazon has revolutionized online shopping with fast delivery, personalized recommendations, and a subscription service called Amazon Prime. It is one of the world's largest and most valuable companies, with a significant impact on retail, technology, and logistics.
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