Data Engineer, Seller Trust Analytics
Seattle, WA, USA
Amazon.com
Free shipping on millions of items. Get the best of Shopping and Entertainment with Prime. Enjoy low prices and great deals on the largest selection of everyday essentials and other products, including fashion, home, beauty, electronics, Alexa...Sellers’ trust in Amazon is our top priority and in this role, you will be tasked with building that trust over time by building and maintaining the data sources that power all of our decision making. Amazon’s growth requires leaders who move fast, have an entrepreneurial spirit to create new solutions, have an unrelenting tenacity to get things done, and are capable of breaking down and solving complex problems.
The successful candidate will be a self-starter, comfortable with ambiguity and be able to create and maintain efficient & automated processes. They know and love working with data engineering tools, can model multidimensional datasets, and can partner effectively with business leaders to build the right data pipelines to answer key business questions. They will build efficient, flexible, extensible, and scalable data models, ETL designs and data integration services. They will also be required to support and manage growth of these data solutions. They are analytical and creative, and don’t quit. This is a role with high visibility to senior leadership and with high opportunity for impact for those willing to roll up their sleeves and dive deep to achieve results.
Key job responsibilities
- Develop data products, infrastructure and data pipelines leveraging AWS services (such as Redshift, Kinesis, EMR, Lambda etc.) and internal Amazon tools.
- Develop new data models and end to data pipelines.
- Collaborate with Senior Data Engineers, BI Analysts, and Software Development Engineers on data delivery best practices.
- Contribute to infrastructure planning and operational excellence continued improvements.
- Participate in design reviews and lead reviews for mid scale solutions.
About the team
The Seller Trust Analytics team supports the entire data infrastructure and insight generation for the Selling Partner Trust organization within Selling Partner Services. We focus on advocating for Sellers and building scalable and innovative solutions to allow Sellers to have long term success on Amazon.
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)
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.
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.
Tags: AWS Big Data Data pipelines DDL Engineering ETL Hadoop HiveQL Informatica Kinesis Lambda Pipelines Python Redshift Scala Spark SQL SSIS
Perks/benefits: Career development Equity / stock options Flex hours Startup environment
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