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Data Engineer, Ring Agent Platforms
We are looking for a Data Engineer to design, build, and operate the data pipelines, models, and platform infrastructure that power Ring's analytics, science, and AI initiatives. You will own the end-to-end data lifecycle — ingestion, transformation, modeling, quality enforcement, and delivery — ensuring that analysts, scientists, and AI systems have access to reliable, well-structured data at scale.
You will use AI development IDEs and generative AI tooling daily to accelerate your work, and you will build multi-agent solutions that automate common data engineering tasks — pipeline generation, data quality enforcement, testing, and operational response. The goal is to turn repeatable patterns into agent-driven workflows that raise velocity and consistency across the team.
You will also contribute to the shared data platform when needed — improving developer tooling, maintaining infrastructure, and supporting the services that the broader data org depends on.
About the team
The Data and Agents Organization spans data engineering, business intelligence, applied science, and agentic AI. The org is structured into three primary groups: one focused on core data platforms, tooling, and pipeline infrastructure; another focused on AI/ML models, business analytics, shared data models, product analytics, and strategic science initiatives; and a third focused on building a multi-agent AI platform that enables teams to compose, deploy, and orchestrate autonomous AI agents at scale. Capacity is balanced across direct business support, strategic new development, and operational health.
Basic Qualifications
- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience with software development life cycle practices including code reviews, source control, CI/CD, testing, and operational support
- 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, Fire Hose, 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
- Familiarity with at least one agentic AI development IDE
- Experience building or maintaining shared data models, semantic layers, or data contracts
- Familiarity with data governance, cataloging, or lineage tracking
- Experience contributing to shared platform infrastructure, developer tooling, or self-service data services
- Familiarity with observability tooling for data pipelines (logging, metrics, alerting)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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.
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, CA, Hawthorne - 132,100.00 - 178,800.00 USD annually
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About Amazon

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
Employees
Seattle
Headquarters
$1.5T
Valuation
Reviews
10 reviews
3.4
10 reviews
Work-life balance
2.5
Compensation
4.2
Culture
3.0
Career
3.8
Management
2.7
65%
Recommend to a friend
Pros
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Learning and advancement opportunities
Good teamwork and colleagues
Cons
High pressure and long hours
Poor work-life balance
Toxic work culture and management issues
Salary Ranges
4 data points
L2
L6
L3
L4
L5
L2 · Data Analyst L2
0 reports
$108,330
total per year
Base
$43,332
Stock
$54,165
Bonus
$10,833
$75,831
$140,829
Interview experience
6 interviews
Difficulty
4.0
/ 5
Duration
21-35 weeks
Experience
Positive 0%
Neutral 17%
Negative 83%
Interview process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Technical Interview
6
Onsite/Virtual Interviews
Common questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
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