Jobs
FBA is seeking a Data Engineer to build AI-native data infrastructure that embeds intelligence as a foundational feature. If you enjoy innovating and want to contribute to an industry-changing business while building next-generation intelligent data platforms, this role is for you.
Core Responsibilities:
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AI-Native Infrastructure & Real-Time Processing
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Engineer AI-native infrastructure supporting real-time data processing for AI/ML inference, training, and continuous learning
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Build semantic layers and knowledge graphs enabling intelligent query routing and context-aware data access
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Develop infrastructure for agentic AI systems with multi-agent orchestration
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Implement GenAI-powered data quality, entity resolution, and metadata management
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Data-as-a-Product Delivery
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Own end-to-end accountability for data products from ingestion to consumption
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Deliver data products with clear SLAs, quality metrics, and customer satisfaction measures
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Build self-service platforms with embedded governance, lineage, and discovery
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Establish data contracts and APIs for reliable, versioned data consumption
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AWS Infrastructure & Pipeline Engineering
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Manage AWS resources: EC2, Lambda, S3, Redshift, Kinesis, EMR, Sage Maker, Bedrock, Neptune
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Build high-quality pipelines supporting analysts, data scientists, and AI agents
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Implement CDC and event-driven architectures for real-time data availability
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Deploy infrastructure-as-code using CDK/Terraform
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Required Qualifications
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5+ years in data engineering with cloud-native architectures
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Strong AWS expertise (Redshift, S3, Glue, Kinesis, EMR)
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Proven experience with real-time streaming (Kafka, Kinesis, Flink)
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Hands-on AI/ML infrastructure experience (Sage Maker, Bedrock)
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Proficiency in Python, SQL, and infrastructure-as-code
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Preferred Qualifications
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Knowledge graphs (Neptune, Neo4j) and semantic layers
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GenAI applications and LLM integration patterns
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Vector databases and feature stores
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Data mesh and domain-oriented architecture
Build the foundational infrastructure powering next-generation AI-enabled data products at Amazon FBA.
Basic Qualifications
- 3+ years of data engineering experience
- 4+ years of SQL experience
- Experience with data modeling, warehousing and building ETL pipelines
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)
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.
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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
Reviews
2.9
10 reviews
Work Life Balance
2.8
Compensation
3.7
Culture
2.5
Career
2.3
Management
2.1
35%
Recommend to a Friend
Pros
Good pay and compensation
Strong benefits package
Flexible scheduling options
Cons
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
Salary Ranges
2 data points
L2
L3
L4
L5
L6
L2 · Data Analyst L2
0 reports
$108,330
total / year
Base
$43,332
Stock
$54,165
Bonus
$10,833
$75,831
$140,829
Interview Experience
10 interviews
Difficulty
3.7
/ 5
Duration
21-35 weeks
Offer Rate
20%
Experience
Positive 10%
Neutral 10%
Negative 80%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
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