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Description

The Amazon Devices-Demand 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 long-term scalability. You should have a proven track record of simplifying complex data architectures, establishing engineering best practices, and mentoring other engineers. We're looking for someone who can proactively identify and resolve architectural deficiencies while collaborating effectively with cross-functional 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 you'll 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 trade-offs, and can deliver high-impact solutions with limited guidance in our fast-paced, dynamic business environment.

Key job responsibilities

• Lead and define data architecture strategies for Devices Demand Planning, ensuring solutions are scalable, maintainable, and align with long-term 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 long-term 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 cross-functional 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.

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

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 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 $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.