Data Engineer, Conversational Shopping Data Engineering

AI in this role

Intermediate Data Engineer needed to design scalable data products and pipelines powering agentic AI-driven customer experiences.

pythonsqlawsspark

etldata-modelingdatabase-architecturebig-datastreaming-data

Our organization builds the data foundations that power the future of online shopping. With ever expanding selection, and ambient computing looming on the horizon, our mission is to build a new shopping experience, beyond search & browse, helping busy customers easily find low-regret products that meet their in-the-moment need. You will have opportunity to closely work with teams who are building Agentic AI powered CX.

An ideal individual is someone who has deep data engineering skills around ETL, data modeling, database architecture and big data solutions. This individual should have strong business judgement, excellent written and verbal communication skills.

Key job responsibilities
- We're looking for an intermediate-level Data Engineer to design and implement data products and solutions that power our shopping platforms.
- You'll own medium to large data initiatives, participate in architectural discussions, build data systems that can scale to PB and streaming data with 100K TPS
- You will be responsible for building data products that power mission critical analytical reports and metrics for Amazon AI products that are viewed at the highest levels in the organization.
- You should have deep expertise in the design, creation, management, and business use of extremely large datasets.
- This role involves building scalable data systems while maintaining high standards of data quality and reliability.
- You will utilize Agentic AI to build data products and solutions
- You will mentor entry-level engineers.

A day in the life
This data engineer designs, builds, and maintains scalable data pipelines that transform raw information into reliable, high-quality datasets for analytics and machine learning. Each day involves design discussion with engineering teams for instrumentation, seek out innovative approaches to design/update data flows, and collaborating with with other internal teams to integrate your data products with theirs and ensure timely, trustworthy data delivery.

About the team
Our organization builds the data foundations that power the future of online shopping. With ever expanding selection, and ambient computing looming on the horizon, it's time to create a new shopping experience, beyond search & browse, helping busy customers easily find low-regret products that meet their in-the-moment need. It's time to leverage big data and machine learning to generate relevant and trustworthy recommendations for billions of shopping journeys through billions of products, and to make it easy and natural for customers to discover those recommendations. We are seeking the industry's best to help us create new ways to interact, search and shop.

Basic qualifications

- 3+ years of data engineering experience
- 4+ years of SQL experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience programming with at least one modern language such as C++, C#, Java, Python, Golang, PowerShell, Ruby

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)

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.

How we rate this

Data Engineer, Conversational Shopping Data Engineering at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ETLData ModelingDatabase ArchitectureBig DataStreaming DataPythonSQLAWS

Questions you could be asked

Tell me about a project where etl was part of your work. What did you do?
Tell me about a project where data modeling was part of your work. What did you do?
Tell me about a project where database architecture was part of your work. What did you do?
Tell me about a project where big data was part of your work. What did you do?
Tell me about a project where streaming data was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: ETL, Data Modeling, Database Architecture, Big Data, and Streaming Data. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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