Data Engineer I, FAE
Seattle, Washington, USA
Full Time Entry-level / Junior USD 91K - 185K
Amazon.com
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Operations Finance Technology team, responsible for building technical solutions for multi-billion WW Operational Cost analytic including Inbound cost (Receiving / PO), variable Cost, fixed cost, outbound (Customer Shipments / Transportation), and Customer Service, is looking for a Data Engineer.
As a data engineer, you will get the exciting opportunity to work on very large data sets in one of the world's largest and most complex data warehouse environments. You will work closely with the business teams in analysis on various cost savings initiatives, many non-standard and unique business problems and use creative-problem solving to deliver actionable output.
You will be responsible for designing and implementing an analytical environment using third-party and in-house reporting tools, modeling metadata, building reports and dashboards. You will have an opportunity to work with leading edge technologies like Redshift, Hadoop/Hive/Pig. You will be writing scalable queries and tuning performance on queries running over billion of rows of data.
- 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)
- 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.
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 $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.
As a data engineer, you will get the exciting opportunity to work on very large data sets in one of the world's largest and most complex data warehouse environments. You will work closely with the business teams in analysis on various cost savings initiatives, many non-standard and unique business problems and use creative-problem solving to deliver actionable output.
You will be responsible for designing and implementing an analytical environment using third-party and in-house reporting tools, modeling metadata, building reports and dashboards. You will have an opportunity to work with leading edge technologies like Redshift, Hadoop/Hive/Pig. You will be writing scalable queries and tuning performance on queries running over billion of rows of data.
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.
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 $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.
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Category:
Engineering Jobs
Tags: Big Data Data warehouse DDL Engineering ETL Finance Hadoop HiveQL Informatica Pipelines Python Redshift Scala Spark SQL SSIS
Perks/benefits: Equity / stock options
Region:
North America
Country:
United States
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