DESCRIPTION

AWS Applications and Higher Level Abstractions (Apps) provides horizontal and industry vertical applications for business users with the same on-demand scalability, reliability, pay-as-you-go pricing, and machine learning expertise that drive AWS services. The AWS Applications group includes services such as Amazon Connect (a cost-effective cloud contact center), our End User Computing (including Amazon Workspaces, AppStream, etc.), Marketing Tech (Amazon Pinpoint), and Autonomous Checkout and Identity Services (Just Walk Out, Amazon One) for retail, sports, travel, and other verticals.

The AWS Just Walk Out Tech organization is seeking a talented Data Engineer to join our team. In this role, you will play a critical part in designing, building, and maintaining scalable data pipelines and architectures that power the Analytics our innovative checkout-free shopping experience. You will work with both internal data and external Retailer-facing reports, ensuring the efficient and reliable flow of data across various systems.

Key job responsibilities
– Design, develop, and maintain high-performance, fault-tolerant data pipelines that process and transform large volumes of structured and unstructured data from multiple sources.
– Implement automated data ingestion, transformation, and loading processes using industry-standard tools and technologies.
– Ensure data quality, integrity, and consistency across the entire data lifecycle.
– Collaborate with fellow Data Engineers, cross-functional stakeholders, including Researchers, Customer Success Managers, Software & ML Engineers, Product Managers, and Technical Program Managers, to define and implement robust data architectures that support Just Walk Out’s business requirements.
– Lead the evolution of our data platform, develop and implement data governance policies, standards, and best practices to ensure data security, privacy, and compliance.
– Design and maintain efficient data models for analytical and operational purposes, considering scalability, performance, and data integration requirements.
– Implement robust monitoring and alerting systems to ensure the health and performance of data pipelines and infrastructure.
– Identify and resolve data-related issues, bottlenecks, and inefficiencies, continuously optimizing data processes and systems.
– Provide technical guidance and mentorship to junior engineers, fostering knowledge sharing and continuous learning.
– Document data architectures, pipelines, and processes to ensure maintainability and knowledge transfer.

About the team
The Just Walk Out team at Amazon is dedicated to revolutionizing the retail experience through cutting-edge technology that enables checkout-free shopping. Our mission is to provide customers with a seamless, convenient, and hassle-free shopping experience by leveraging advanced computer vision, sensor fusion, and machine learning algorithms. We foster a culture of innovation, collaboration, and customer obsession, where talented individuals from diverse backgrounds come together to tackle complex challenges. With a start-up mindset and an entrepreneurial spirit, we embrace risk-taking, experimentation, and continuous learning. Our team values open communication, knowledge sharing, and a supportive environment that encourages personal and professional growth. We strive to push the boundaries of what’s possible, constantly seeking new ways to delight our customers and shape the future of retail.

Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

BASIC QUALIFICATIONS

– 3+ years of data engineering experience
– Experience with data modeling, warehousing and building ETL pipelines

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)