Description
- Bachelor's degree
- 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
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $91,200/year in our lowest geographic market up to $185,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Come and be part of the International Seller Services (ISS) Central Analytics Data Engineering (DE) team and work on solving cutting edge 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 large 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
- 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
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $91,200/year in our lowest geographic market up to $185,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Come and be part of the International Seller Services (ISS) Central Analytics Data Engineering (DE) team and work on solving cutting edge 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 large 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
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