Data Engineer III, Partner Experience and Growth, Amazon Ads

Amazon; New York (NY); Presencial; USD 139 100 - 240 500; Tempo integral

Resumo da oferta

Amazon is seeking a Data Engineer III to join the Partner Experience and Growth team. This role involves designing and implementing data structures for analytics and building end-to-end data solutions while collaborating with various teams to enhance data-driven decision-making. Ideal candidates should have strong experience in data engineering, ETL pipelines, and SQL, with a Master's degree preferred. The base salary ranges from $139,100 to $240,500, depending on market location and experience.

Qualificações

• 5+ years of data engineering experience.
• Experience mentoring team members on best practices.
• 7+ years of data engineering or related experience preferred.

Responsabilidades

• Design, implement and operate large-scale data structures for analysis.
• Implement data ingestion routines using best practices.
• Collaborate with teams to create efficient algorithms for data insights.

Conhecimentos

Data modeling

ETL pipelines

SQL

Python

Data integrity

Formação académica

Master's degree in Computer Science or related field

Ferramentas

Hadoop

Hive

Spark

EMR

Descrição da oferta de emprego

Data Engineer III, Partner Experience and Growth, Amazon Ads

Job ID: 2876610 | Amazon.com Services LLC

Amazon Worldwide Advertising is one of Amazon's fastest growing and most profitable businesses. Partner Experience and Growth (PEG) organization leverages advanced analytics and experimentation to unlock value for our advertising partners and mutual customers, i.e. the advertisers.

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 strive for simplicity, demonstrate creativity and sound judgement. You deliver data solutions that are customer focused, easy to consume and create business impact.

Key job responsibilities
Design, implement and operate large-scale, high-volume, high-performance data structures for analytics and data science.
Implement data ingestion routines both real time and batch 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.
Collaborate with scientists to create fast and efficient algorithms that exploit our rich data sets for optimization, statistical analysis, prediction, clustering, and machine learning.
Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for customers.

About the team
Data Engineering team focuses on helping other partner business teams to be a more data driven business. We synthesize data from various data sources into actionable information, help the team to build the insights and take business decisions. We maintain partner data platform(Barnegat) and support end to end data engineering needs for our customers. Data engineering team customers include Analytics, Science, Finance, Partner Trust, Business Development, Product and other Advertisement teams. Our core services are managing Data platform, data pipelines to get data from various sources, create scalable and reusable datasets and provide single source of truth for business metrics.

BASIC QUALIFICATIONS

- 5+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience mentoring team members on best practices

PREFERRED QUALIFICATIONS

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience operating large data warehouses
- 7+ years of data engineering, database engineering, business intelligence or business analytics experience
- Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
- Experience in working with data, analytics and reporting related to risk management, fraud detection, and customer trust/identity verification.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $139,100/year in our lowest geographic market up to $240,500/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.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.