About the role

Design, implement, and automate scalable data pipelines while ensuring data accuracy and consistency across the platform. Collaborate with cross-functional stakeholders to translate business requirements into reliable data solutions and resolve root causes of data defects.

What they look for

Data engineering Data modeling Data warehousing ETL pipelines SQL Python Redshift Glue Data quality AWS infrastructure Data schema design Normalization Relational modeling Dimensional modeling Scala HiveQL

Requirements

Requires experience in data engineering, data modeling, and building ETL pipelines. Proficiency in query languages like SQL and scripting languages such as Python is essential.

Benefits

Professional development Mentorship Career growth opportunities

Full description

Do you love building scalable data pipelines and engineering reliable datasets? Are you excited by the opportunity to create foundational data infrastructure that powers decision-making across a complex logistics network? Do you want to work in a fast-paced environment, solving data challenges at the intersection of engineering and business impact?

If this describes you, consider joining us. You will have the opportunity to work alongside the industry's brightest engineers, who innovate every day on behalf of our customers. You will have the opportunity to affect the evolution of Amazon technology, as well as lead mission-critical projects. Your work will contribute to solving some of the most complex technical challenges in the company.

In addition to working on impactful projects, you will have the opportunity to engage with Amazonians for both personal and professional development and expand your network.

Come chart your own path at Amazon.

Key job responsibilities - Design, implement, and automate scalable data pipelines for collecting, transforming, and processing data from multiple sources (Redshift, Glue) - Design and evolve data models and schemas ensuring accuracy, consistency, and alignment with single source of truth standards - Own the development and maintenance of curated reference datasets and data assets to drive key business decisions - Monitor and troubleshoot data quality issues and operational incidents in production pipelines - Drive architectural plans and implementation for future data storage and integration solutions - Collaborate with stakeholders across operations, finance, and science to translate business requirements into reliable data solutions - Investigate and resolve root causes of data defects, ensuring data accuracy and reliability across the platform

A day in the life Our Data Engineers build and maintain the infrastructure to answer questions with data, using software engineering best practices, data management fundamentals, and data storage principles.

Work/Life Balance Our team puts a high value on work-life balance. It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfilment.

Inclusive Team Culture Our team is intentional about attracting, developing, and retaining amazing talent from diverse backgrounds. Yes, we do get to build really cool data solutions, but we also think a big reason for that is the inclusive and welcoming culture we try to cultivate every day.

Mentorship & Career Growth We care about your career growth. Whether your goals are to explore new technologies, take on bigger opportunities, or get to the next level, we'll help you get there. Our business is growing fast and our people will grow with it.

About the team MINT (Miles Intelligence and Truth), within Supply Chain Execution Data & Analytics, delivers end-to-end data solutions for EU Transportation. We are the Single Source of Truth (SSOT) team - creating and owning the trusted reference datasets across different EU Transportation areas. We build scalable pipelines and self-service tools that drive data-driven decisions across the organisation.

Basic Qualifications: - Experience in data engineering - 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 any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc. - Knowledge of basics of designing and implementing a data schema like normalization, relational model vs dimensional model - Knowledge of AWS Infrastructure

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

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.