Data Engineer II

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.

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, 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)

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