Data Engineer II
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Job Location:
Monthly Salary:
Posted on:
3 days ago
Vacancies:
1 Vacancy
Department:
Job Summary
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.
- 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 for more information. If the country/region youre applying in isnt 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.
- 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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Required Experience:
IC
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
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