Snr Data Engineer, Amazon Prime
Seattle, Washington
Amazon Prime's Science organization leads the Research & Development towards innovation for Amazon Prime. Amazon Prime is the backbone of Amazon's consumer business and aspires to be the world's most engaging, satisfying, and loved membership program, driving growth and profitability. The program serves over 200 million members across 25 countries and is key to Amazon's customer growth and engagement. Prime Science innovates in Artificial Intelligence and Economics, to develop algorithms and systems for automated marketing, personalization, targeting, and decisioning. Within the engineering group in Prime Science, we develop world class solutions to complex scientific and engineering problems at Amazon scale. You will work alongside world class scientists to build a suite of fully automated, scalable and robust products driven by the data systems you develop.
Do you want to work with the worlds best engineers at massive scale on hard problems? Do you want to be impact over 200 million Prime members WW? Do you want to learn the latest AWS and big data technologies to build cutting-edge science products? Are you someone who likes using big data to drive high-impact business decisions? If the answer is yes, come join our team!
Key job responsibilities
- Build big data pipelines for machine learning applications at Amazon scale
- Advance the state of data engineering infrastructure on the latest tools (AWS Glue, Spark, AWS EMR, EMR Serverless, Ray etc...)
- Improve and raise the bar on proactive data quality monitoring and alarming (e.g., anomaly detection) across big data pipelines
- Work alongside science to enhance data pipelines that feed models improving the customer experience of over 200MM customers world wide.
- Defining the future of Prime Science data architecture
A day in the life
As a data engineer on this team, you will collaborate closely with Prime business leaders, scientists (economists, research scientists, applied scientists) and engineering leaders to build data solutions. You will leverage AWS technologies (EMR, EC2, S3, GLUE, KMS, Lambda, DynamoDB, etc.) to build novel systems and tackle challenges at scale. You will manipulate and process TB-sized data, supporting real-time access and orchestration across multiple systems. Your work will enhance our scientific models and data applications. As a consequence, you will have global impact, improving customer experiences for Prime members worldwide. As a successful candidate, you will successfully interact with both technical and business stakeholders.
About the team
Our team has a vision to enable Prime Science to be adopted WW across Amazon so as to drive the best possible customer experience. We set and raise engineering excellence standards in Amazon for science-based products. We are a unique team as we sit at the intersection of building engineering systems at Amazon scale and availability, incorporating the latest science (econometrics, ML, AI etc...), and delivering cross-cutting applications to delight over 200 million customers. Building and our science products at-scale and in real-time, creates interesting new data engineering challenges. These give a person in this role a head start in solving artificial intelligence challenges that will be ubiquitous 3-5 years from now.
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
- Knowledge of distributed systems as it pertains to data storage and computing
- Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
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 $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.
Do you want to work with the worlds best engineers at massive scale on hard problems? Do you want to be impact over 200 million Prime members WW? Do you want to learn the latest AWS and big data technologies to build cutting-edge science products? Are you someone who likes using big data to drive high-impact business decisions? If the answer is yes, come join our team!
Key job responsibilities
- Build big data pipelines for machine learning applications at Amazon scale
- Advance the state of data engineering infrastructure on the latest tools (AWS Glue, Spark, AWS EMR, EMR Serverless, Ray etc...)
- Improve and raise the bar on proactive data quality monitoring and alarming (e.g., anomaly detection) across big data pipelines
- Work alongside science to enhance data pipelines that feed models improving the customer experience of over 200MM customers world wide.
- Defining the future of Prime Science data architecture
A day in the life
As a data engineer on this team, you will collaborate closely with Prime business leaders, scientists (economists, research scientists, applied scientists) and engineering leaders to build data solutions. You will leverage AWS technologies (EMR, EC2, S3, GLUE, KMS, Lambda, DynamoDB, etc.) to build novel systems and tackle challenges at scale. You will manipulate and process TB-sized data, supporting real-time access and orchestration across multiple systems. Your work will enhance our scientific models and data applications. As a consequence, you will have global impact, improving customer experiences for Prime members worldwide. As a successful candidate, you will successfully interact with both technical and business stakeholders.
About the team
Our team has a vision to enable Prime Science to be adopted WW across Amazon so as to drive the best possible customer experience. We set and raise engineering excellence standards in Amazon for science-based products. We are a unique team as we sit at the intersection of building engineering systems at Amazon scale and availability, incorporating the latest science (econometrics, ML, AI etc...), and delivering cross-cutting applications to delight over 200 million customers. Building and our science products at-scale and in real-time, creates interesting new data engineering challenges. These give a person in this role a head start in solving artificial intelligence challenges that will be ubiquitous 3-5 years from now.
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
- Knowledge of distributed systems as it pertains to data storage and computing
- Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
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 $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.
Created: 2024-08-30
Reference: 2748539
Country: United States
State: Washington
City: Seattle
ZIP: 98109
About Amazon
Founded in: 1994
Number of Employees: 1600000
Website: https://www.amazon.com/
Career site: https://www.amazon.jobs/en/
Instagram: https://www.instagram.com/amazon/
LinkedIn: https://www.linkedin.com/company/amazon/
Facebook: https://www.facebook.com/Amazon
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