Retail Business Services (RBS) supports Amazon's Retail business growth worldwide through three core tasks. These are (a) Selection, where RBS sources, creates and enriches ASINs to drive Gross Merchandise Sales (GMS) growth; (b) Defect Elimination: where RBS resolves inbound supply chain defects and develops root cause fixes to improve free cash flow and (c) supports operational processes for Worldwide Retail teams.
Our Team
We have a team of high-caliber software developers, applied scientists, data engineers, product managers, and Business Intelligence Engineers who use rigorous machine learning and deep learning approaches to ensure that we identify and fix the right catalog defect to provide a good shopping experience for our customers.
Your Role
As a Data Engineer, you will own and deliver data engineering initiatives and build end-to-end analytical solutions that are highly available, scalable, stable, secure, and cost-effective. You will strive for simplicity, demonstrate creativity, and sound judgment. You will deliver data solutions that are customer-focused, easy to consume, and create business impact.
You will be passionate about working with huge datasets and have experience with organizing and curating data for analytics. You will have a strategic and long-term view on architecting advanced data ecosystems. You will be experienced in building efficient and scalable data services and have the ability to integrate data systems with AWS tools and services to support various customer use cases and applications.
Key Responsibilities
1. Implement data ingestion routines both real-time and batch using best practices in data modeling, Extract Transform Load/Extract Load Transform (ETL/ELT) processes by leveraging AWS technologies and big data tools.
2. Design, implement, and operate large-scale, high-volume, high-performance data for analysis and data science.
3. Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.
4. Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for customers.
Requirements
BASIC QUALIFICATIONS
* 1+ years of data engineering experience
* Experience with Structured Query Language (SQL)
* Experience with data modeling, warehousing, and building ETL pipelines
* Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
* Experience with one or more scripting languages (e.g., Python, KornShell)
PREFERRED QUALIFICATIONS
* Experience with big data technologies such as Hadoop, Hive, Spark, Amazon Elastic MapReduce (EMR)
* Experience with any ETL tool like Informatica, Oracle Data Integrator (ODI), SQL Server Integration Services (SSIS), BODI, DataStage, etc.
About Our Inclusive Culture
We have an inclusive culture that 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 this link for more information.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.