Overview
Do you enjoy diving deep into data, developing real-time and batch pipelines that generate actionable insights? The DSP Analytics team has an exciting opportunity for a Data Engineer to make impactful contributions to Amazon's Delivery Service Partner (DSP) program tackling modern data challenges by combining traditional engineering practices with transformative analytics and Generative AI. You'll help design and build the next generation of data infrastructure powering GenAI applications, and develop agents that automate the end-to-end data operations lifecycle. We are a team of Data Engineers working closely with Data Scientists, Economists, and Analysts turning machine learning and AI research into scalable products that delight customers worldwide. You're passionate about technology, strongly biased toward going deep to find insights, and driven to build scalable analytical platforms
Full job description
Full Job Description
Do you enjoy diving deep into data, developing real-time and batch pipelines that generate actionable insights? The DSP Analytics team has an exciting opportunity for a Data Engineer to make impactful contributions to Amazon's Delivery Service Partner (DSP) program tackling modern data challenges by combining traditional engineering practices with transformative analytics and Generative AI.
You'll help design and build the next generation of data infrastructure powering GenAI applications, and develop agents that automate the end-to-end data operations lifecycle. We are a team of Data Engineers working closely with Data Scientists, Economists, and Analysts turning machine learning and AI research into scalable products that delight customers worldwide.
You're passionate about technology, strongly biased toward going deep to find insights, and driven to build scalable analytical platforms. You're relentless about quality and reliability, and comfortable communicating across different levels of leadership. If that sounds like you, we'd love to talk.
Key job responsibilities • Lead and design complex data architectures, ensuring scalability, security, and alignment with business objectives • Drive implementation of large-scale data pipelines and ETL processes using AWS technologies • Identify and resolve system-wide data challenges, including performance bottlenecks and architectural deficiencies • Establish data engineering best practices, including governance, security standards, and operational excellence • Ensure data solutions are auditable, accessible, and maintainable across the organization • Collaborate with cross-functional teams to deliver innovative data solutions
About the team We are the Amazon DSP Analytics team, supporting all business pillars across the DSP organization horizontally, with the vision to enable data-, insights-, and science-driven decision-making. We are an exceptionally talented and fun-loving team. Here, you'll have the opportunity to dive deep into complex business and data problems, drive large-scale technical solutions, and raise the bar for operational excellence. We love sharing ideas and learning from each other, and we believe in using those ideas to disrupt the status quo.
Basic Qualifications
- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Bachelor's degree in Computer Science, Engineering, or related fields
- Experience programming with at least one modern language such as Python, Ruby, Golang, Java, C++, C#, Rust
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Demonstrated use of generative AI tools (e.g., agentic coding assistants, AI-powered IDEs) in a professional or project setting
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 designing or building AI agents or multi-agent solutions that automate engineering workflows
- Familiarity with agentic AI patterns including tool use, function calling, and multi-agent orchestration
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.
Requirements & qualifications
3+ years of data engineering experience Experience with data modeling, warehousing and building ETL pipelines Bachelor's degree in Computer Science, Engineering, or related fields Experience programming with at least one modern language such as Python, Ruby, Golang, Java, C++, C#, Rust 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience Demonstrated use of generative AI tools (e.g., agentic coding assistants, AI-powered IDEs) in a professional or project setting
Tips for this job
Practical Job and Scholarship guidance. These tips do not replace official rules or create new eligibility requirements.
- Tailor the CV and application to the responsibilities and required skills stated on the official employer page.
- Use concrete evidence of relevant work, projects and measurable results rather than generic claims.
- Confirm location, work authorization, remote restrictions and sponsorship terms before applying.
- Apply through the original employer or official recruitment destination shown on this page.
Verification notes
Public Amazon careers search record with employer description and structured locations.
Job and Scholarship is the discovery and verification layer. Confirm eligibility, dates, salary/funding and application instructions on the original source before submitting anything.
Amazon ↗