Amazon

DESCRIPTION

Are you passionate about building data products that power strategic insights? Do you enjoy thinking end-to-end—from raw data to analytics-ready pipelines? If you’re excited by the challenge of designing scalable data infrastructure that enables decision-making at scale, we’d love to talk to you.

We are a data and analytics engineering team embedded in the Finance organization, supporting AWS Infrastructure Services & Supply Chain Finance (AIS SCF). We own a broad portfolio of valuable datasets and are investing in modernizing our data infrastructure to enable deeper analytics, better self-service, and stronger business impact. Our vision is to build a high-quality data foundation that accelerates insight generation and enables long-term product innovation.

We are looking for an Analytics-focused Data Engineer who is as passionate about clean, scalable data systems as they are about understanding the business context behind the numbers. In this role, you’ll partner closely with data engineers, BIEs, and product managers, as well as finance and business stakeholders. You’ll work across data platforms, transformation frameworks, orchestration tools, data modeling, and visualization systems—to build solutions that deliver trusted data at scale.

The ideal candidate combines technical strength with business curiosity: someone who enjoys exploring systems and processes independently, understands how data reflects business performance, and wants to shape how data informs strategy. You should be comfortable working in ambiguity, learning new technologies, and communicating clearly with both technical and non-technical audiences. If you want to make an impact by building data products that inform decisions and drive innovation, this is the role for you.

Key job responsibilities

• Design, build, and maintain scalable, reliable, and reusable data pipelines and infrastructure that support analytics, reporting, and strategic decision-making.
• Develop data models and prepare datasets that are intuitive, well-documented, and aligned with both immediate business needs and long-term analytical goals.
• Partner with Business Intelligence Engineers, product managers, and finance stakeholders to translate ambiguous business questions into clear data solutions that inform strategy.
• Explore source systems, data flows, and business processes to uncover opportunities, ensure data accuracy and completeness, and drive improvements in data quality and usability.
• Take end-to-end responsibility for the datasets you own—ensuring they are well-documented, meet user needs, and continuously evolve as business requirements change.
• Enable self-service analytics by delivering high-quality, trusted datasets and promoting best practices in data access and usage.
• Continuously identify opportunities to improve data flow efficiency, reduce technical debt, and simplify data architecture.
• Stay current with evolving data technologies and evaluate new tools and frameworks to improve our data platform’s scalability and performance.
• Continuously look for ways to improve our data tools, practices, and pipelines to better support insight generation and strategic decision-making.

About the team

https://w.amazon.com/bin/view/IFBIT

BASIC QUALIFICATIONS

• 3+ 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
• Strong analytical skills, with the ability to translate business requirements into technical data solutions.
• Excellent communication skills, with the ability to collaborate across technical and business teams.

PREFERRED QUALIFICATIONS

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
• Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets
• Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
• 3+ years of reparation of data for direct use in visualization tools like Tableau experience
• Strong business acumen with a focus on how data supports decision-making and strategic initiatives.

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 $118,900/year in our lowest geographic market up to $205,600/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.