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Job Description
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:
AI-Native Infrastructure & Real-Time Processing
- Engineer AI-native infrastructure supporting real-time data processing for AI/ML inference, training, and continuous learning
- Build semantic layers and knowledge graphs enabling intelligent query routing and context-aware data access
- Develop infrastructure for agentic AI systems with multi-agent orchestration
- Implement GenAI-powered data quality, entity resolution, and metadata management
Data-as-a-Product Delivery
- Own end-to-end accountability for data products from ingestion to consumption
- Deliver data products with clear SLAs, quality metrics, and customer satisfaction measures
- Build self-service platforms with embedded governance, lineage, and discovery
- Establish data contracts and APIs for reliable, versioned data consumption
AWS Infrastructure & Pipeline Engineering
- Manage AWS resources: EC2, Lambda, S3, Redshift, Kinesis, EMR, SageMaker, Bedrock, Neptune
- Build high-quality pipelines supporting analysts, data scientists, and AI agents
- Implement CDC and event-driven architectures for real-time data availability
- Deploy infrastructure-as-code using CDK/Terraform
Required Qualifications
- 5+ years in data engineering with cloud-native architectures
- Strong AWS expertise (Redshift, S3, Glue, Kinesis, EMR)
- Proven experience with real-time streaming (Kafka, Kinesis, Flink)
- Hands-on AI/ML infrastructure experience (SageMaker, Bedrock)
- Proficiency in Python, SQL, and infrastructure-as-code
Preferred Qualifications
- Knowledge graphs (Neptune, Neo4j) and semantic layers
- GenAI applications and LLM integration patterns
- Vector databases and feature stores
- Data mesh and domain-oriented architecture
Build the foundational infrastructure powering next-generation AI-enabled data products at Amazon FBA.
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
- 3+ years of data engineering experience
- 4+ years of SQL experience
- Experience with data modeling, warehousing and building ETL pipelines
- 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.
Core Responsibilities:
AI-Native Infrastructure & Real-Time Processing
- Engineer AI-native infrastructure supporting real-time data processing for AI/ML inference, training, and continuous learning
- Build semantic layers and knowledge graphs enabling intelligent query routing and context-aware data access
- Develop infrastructure for agentic AI systems with multi-agent orchestration
- Implement GenAI-powered data quality, entity resolution, and metadata management
Data-as-a-Product Delivery
- Own end-to-end accountability for data products from ingestion to consumption
- Deliver data products with clear SLAs, quality metrics, and customer satisfaction measures
- Build self-service platforms with embedded governance, lineage, and discovery
- Establish data contracts and APIs for reliable, versioned data consumption
AWS Infrastructure & Pipeline Engineering
- Manage AWS resources: EC2, Lambda, S3, Redshift, Kinesis, EMR, SageMaker, Bedrock, Neptune
- Build high-quality pipelines supporting analysts, data scientists, and AI agents
- Implement CDC and event-driven architectures for real-time data availability
- Deploy infrastructure-as-code using CDK/Terraform
Required Qualifications
- 5+ years in data engineering with cloud-native architectures
- Strong AWS expertise (Redshift, S3, Glue, Kinesis, EMR)
- Proven experience with real-time streaming (Kafka, Kinesis, Flink)
- Hands-on AI/ML infrastructure experience (SageMaker, Bedrock)
- Proficiency in Python, SQL, and infrastructure-as-code
Preferred Qualifications
- Knowledge graphs (Neptune, Neo4j) and semantic layers
- GenAI applications and LLM integration patterns
- Vector databases and feature stores
- Data mesh and domain-oriented architecture
Build the foundational infrastructure powering next-generation AI-enabled data products at Amazon FBA.
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
- 3+ years of data engineering experience
- 4+ years of SQL experience
- Experience with data modeling, warehousing and building ETL pipelines
- 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.