Data Engineer I
Data Engineer I
Posted on :
02-05-2025
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1 Vacancy
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Job Description
Do you have the technical skill to build BI solutions that process billions of rows a day using AWS technologies Do you want to create nextgeneration tools for intuitive data access Do you wake up in the middle of the night with new ideas that will benefit your customers Are you persistent in bringing your ideas to fruition
First things first you know SQL and data modelling like the back of your hand. You also need to know Big Data and MPP systems. You have a history of coming up with innovative solutions to complex technical problems. You are a quick and willing learner of new technologies and have examples to prove your aptitude. You are not toolcentric; you determine what technology works best for the problem at hand and apply it accordingly. You can explain complex concepts to your nontechnical customers in simple terms.
Key job responsibilities
Work with SDE teams and business stakeholders to understand data requirements and design data ingress flow for team
Lead the design model and implementation of large evolving structured semistructured and unstructured datasets
Evaluate and implement efficient distributed storage and query techniques
Interact and integrate with internal and external teams and systems to extract transform and load data from a wide variety of sources
Implement robust and maintainable code with clear and maintained documentation
Implement test automation on code implemented through unit testing and integration testing
Work in a tech stack which is a mix of NAWS services and legacy ETL tools within Amazon
About the team
Data Insights Metrics & Reporting team (DIMR) is the central data engineering team in Amazon Warehousing & Distribution org which is responsible for 4 things mainly
Building and maintaining data engineering and reporting infrastructure using NAWS to support internal/external data usecases.
Building data ingestions pipelines from any kind of upstream data sources which include (but not limited to) real time event streaming services data lakes manual file uploads etc.
Building mechanisms to vend data to internal team members or external sellers with right data handling techniques in place.
Build robust data mart to support diverse usecases powered by GenAI tool.
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 big data technologies such as: Hadoop Hive Spark EMR
Experience with any ETL tool like Informatica ODI SSIS BODI Datastage etc.
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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
First things first you know SQL and data modelling like the back of your hand. You also need to know Big Data and MPP systems. You have a history of coming up with innovative solutions to complex technical problems. You are a quick and willing learner of new technologies and have examples to prove your aptitude. You are not toolcentric; you determine what technology works best for the problem at hand and apply it accordingly. You can explain complex concepts to your nontechnical customers in simple terms.
Key job responsibilities
Work with SDE teams and business stakeholders to understand data requirements and design data ingress flow for team
Lead the design model and implementation of large evolving structured semistructured and unstructured datasets
Evaluate and implement efficient distributed storage and query techniques
Interact and integrate with internal and external teams and systems to extract transform and load data from a wide variety of sources
Implement robust and maintainable code with clear and maintained documentation
Implement test automation on code implemented through unit testing and integration testing
Work in a tech stack which is a mix of NAWS services and legacy ETL tools within Amazon
About the team
Data Insights Metrics & Reporting team (DIMR) is the central data engineering team in Amazon Warehousing & Distribution org which is responsible for 4 things mainly
Building and maintaining data engineering and reporting infrastructure using NAWS to support internal/external data usecases.
Building data ingestions pipelines from any kind of upstream data sources which include (but not limited to) real time event streaming services data lakes manual file uploads etc.
Building mechanisms to vend data to internal team members or external sellers with right data handling techniques in place.
Build robust data mart to support diverse usecases powered by GenAI tool.
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 big data technologies such as: Hadoop Hive Spark EMR
Experience with any ETL tool like Informatica ODI SSIS BODI Datastage etc.
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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Employment Type
Full-Time
Department / Functional Area
Key Skills
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