Sr. Data Engineer, Amazon Devices-Demand Planning
Sr. Data Engineer, Amazon Devices-Demand Planning
Posted on :
09-05-2025
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1 Vacancy
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Job Description
The Amazon DevicesDemand Planning team is seeking a Senior Data Engineer who will serve as a technical leader in designing and implementing robust data architecture solutions. In this role you will drive the evolution of our data infrastructure architecting scalable solutions that support critical business analytics and machine learning initiatives. You will lead the development of sophisticated ETL pipelines and data warehousing solutions using AWS technologies including Redshift S3 Glue SNS and Lambda while ensuring data quality accessibility and security.
The ideal candidate excels at breaking down complex technical challenges into manageable components anticipating future data access patterns and implementing solutions that balance immediate business needs with longterm scalability. You should have a proven track record of simplifying complex data architectures establishing engineering best practices and mentoring other engineers. Were looking for someone who can proactively identify and resolve architectural deficiencies while collaborating effectively with crossfunctional teams including Software Engineers Data Scientists Product Managers and BI Engineers.
You will be responsible for driving technical strategy making architectural decisions and building consensus across teams. Strong communication skills are essential as youll be expected to influence technical decisions mentor team members and articulate complex technical concepts to diverse stakeholders. The role requires someone who thrives in ambiguous environments demonstrates excellent judgment in technical tradeoffs and can deliver highimpact solutions with limited guidance in our fastpaced dynamic business environment.
Key job responsibilities
Lead and define data architecture strategies for Devices Demand Planning ensuring solutions are scalable maintainable and align with longterm business objectives.
Design implement and optimize complex data pipelines and ETL processes while establishing best practices and standards for data engineering across the team.
Drive technical decisions and architectural improvements that enhance data quality accessibility and performance across multiple systems and teams.
Proactively identify and resolve systemic data architecture deficiencies including breaking down large initiatives into parallel workstreams that can be executed by multiple team members.
Mentor and provide technical guidance to other data engineers conducting technical assessments and contributing to the professional development of team members.
Partner with product managers data scientists and other stakeholders to translate business requirements into robust technical solutions while maintaining a balance between immediate needs and longterm architectural goals.
Manage and optimize AWS infrastructure resources (S3 Redshift Glue etc.) ensuring operational excellence cost efficiency and scalability.
Drive data governance initiatives including establishing data security protocols naming conventions and documentation standards across the organization.
Influence and build consensus across teams when implementing crossfunctional data solutions and architectural changes.
About the team
Data Engineering team within Demand Planning supports Data Infrastructure Data Architecture and Data Management functions. This includes sourcing ingesting and processing of large datasets; building and optimizing logical and physical data models; curation of Input data for forecasting models publishing data and enhancing data management solutions supporting Demand Forecasting models and reporting tools.
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
Experience with big data technologies such as: Hadoop Hive Spark EMR
Experience operating large data warehouses
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 for more information. If the country/region youre applying in isnt 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 $139100/year in our lowest geographic market up to $240500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon 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 This position will remain posted until filled. Applicants should apply via our internal or external career site.
The ideal candidate excels at breaking down complex technical challenges into manageable components anticipating future data access patterns and implementing solutions that balance immediate business needs with longterm scalability. You should have a proven track record of simplifying complex data architectures establishing engineering best practices and mentoring other engineers. Were looking for someone who can proactively identify and resolve architectural deficiencies while collaborating effectively with crossfunctional teams including Software Engineers Data Scientists Product Managers and BI Engineers.
You will be responsible for driving technical strategy making architectural decisions and building consensus across teams. Strong communication skills are essential as youll be expected to influence technical decisions mentor team members and articulate complex technical concepts to diverse stakeholders. The role requires someone who thrives in ambiguous environments demonstrates excellent judgment in technical tradeoffs and can deliver highimpact solutions with limited guidance in our fastpaced dynamic business environment.
Key job responsibilities
Lead and define data architecture strategies for Devices Demand Planning ensuring solutions are scalable maintainable and align with longterm business objectives.
Design implement and optimize complex data pipelines and ETL processes while establishing best practices and standards for data engineering across the team.
Drive technical decisions and architectural improvements that enhance data quality accessibility and performance across multiple systems and teams.
Proactively identify and resolve systemic data architecture deficiencies including breaking down large initiatives into parallel workstreams that can be executed by multiple team members.
Mentor and provide technical guidance to other data engineers conducting technical assessments and contributing to the professional development of team members.
Partner with product managers data scientists and other stakeholders to translate business requirements into robust technical solutions while maintaining a balance between immediate needs and longterm architectural goals.
Manage and optimize AWS infrastructure resources (S3 Redshift Glue etc.) ensuring operational excellence cost efficiency and scalability.
Drive data governance initiatives including establishing data security protocols naming conventions and documentation standards across the organization.
Influence and build consensus across teams when implementing crossfunctional data solutions and architectural changes.
About the team
Data Engineering team within Demand Planning supports Data Infrastructure Data Architecture and Data Management functions. This includes sourcing ingesting and processing of large datasets; building and optimizing logical and physical data models; curation of Input data for forecasting models publishing data and enhancing data management solutions supporting Demand Forecasting models and reporting tools.
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
Experience with big data technologies such as: Hadoop Hive Spark EMR
Experience operating large data warehouses
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 for more information. If the country/region youre applying in isnt 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 $139100/year in our lowest geographic market up to $240500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon 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 This position will remain posted until filled. Applicants should apply via our internal or external career site.
Required Experience:
Senior IC
Employment Type
Full-Time
Department / Functional Area
Key Skills
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