As a Data Engineer on the Shopbop team you will routinely solve complex data problems, unblocking critical projects that drive Shopbop's mission to be "the daily destination for style inspiration and discovery." Whether you are optimizing analytics that help marketing tune their strategies, building new pipelines to speed up delivery, partnering with our Science team to deliver AI solutions, or helping accounting drill down to track our business: your work will empower meaningful change for your customers. You will partner closely with stakeholders across the business and with the Data Engineering team to deliver new features, or pitch in to migrate legacy features to a modern AWS-based platform. You will be an active partner in the broader Amazon data engineering community (Amazon is Shopbop's parent company), taking part in learning series and operational reviews with industry-leading engineers.
Shopbop is part of Amazon Fashion, but with a unique vibe and mission to serve fashion-oriented customers. The data engineering team frequently collaborates with teams across the business, providing opportunities to learn about the fashion industry and e-commerce (and employee discounts). We are looking for a candidate willing to be in person at our New York office (JFK94).
Key job responsibilities
You will own projects that build new data pipelines, modernize existing ones onto our AWS-based platform, or refine pipelines to deliver more value for our customers. You will partner with colleagues across Shopbop to understand their business domains and build solutions that meet their needs, including working with our Science team to bring AI solutions to production. You will also be an active participant on the Shopbop data team, driving improvements to the team's operational health and reducing errors for customers. And you will take part in Amazon's engineering culture, learning from and teaching alongside the best, while making the most of AI-powered tools to work more effectively.
Some of your tasks will include:
- Architecting, designing, and implementing next-generation data pipelines and BI solutions built on AWS
- Building and optimizing ETL processes to improve data quality, reliability, and freshness
- Leveraging AI-powered developer and data tools to boost your own productivity and code quality
- Partnering with business stakeholders to translate their needs into scalable data solutions
- Collaborating with the Science team to build data foundations for AI solutions and bring them into production
- Improving the team's operational excellence through monitoring, automation, and error reduction
A day in the life
Your day starts with the team standup, reviewing pipeline health and any overnight data issues alongside fellow Data Engineers and your tech lead. You'll partner directly with these business customers to turn their needs into reliable data solutions. Our team has a strong, collaborative culture: you'll learn continuously from experienced engineers through pairing, design reviews, and you'll share your own expertise in return.
About the team
We are the Shopbop Data Engineering team, the backbone of data-driven decision-making across the business. Our mission is to deliver reliable, high-quality data that powers everything from marketing strategy to shipping optimization to financial reporting. We're in the middle of an exciting transformation, modernizing our legacy Informatica pipelines onto a scalable AWS-based platform. We're also embracing AI: adopting AI-powered tools to boost our own productivity and operational health, and partnering with our Science team to build AI solutions for the business. We value operational excellence, continuous learning, and collaboration.
BASIC QUALIFICATIONS
- 3+ years of data engineering experience
- Bachelor's degree
- Experience operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets, or experience in software development
- Experience in one or more scripting languages (e.g., Python, Ruby, Perl)
PREFERRED QUALIFICATIONS
- Experience working on and delivering end to end projects independently
- Experience in data warehouse technical architectures, data modeling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience in relational database technology (such as Redshift, Oracle, MySQL or MS SQL)
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Experience scripting in modern program languages, or experience operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Knowledge of agile development and best coding practices including peer code reviews, and unit testing
- Experience with Informatica and delivering data platform migration projects
- Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices.
- Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, NY, New York - 145,300.00 - 196,600.00 USD annually
