Data Engineer II
Build AI-native data infrastructure at Amazon FBA with real-time processing, ML pipelines, and AWS services.
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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) 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.