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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.
- 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 you're applying in isn't listed, please contact your Recruiting Partner.
Job ID: 149133229
Skills:
AWS Glue, Sql, ELT, Data Modeling, Pyspark, Etl, Sparksql, Python, Spark, Airflow, dbt, MWAA, alerting, data quality frameworks, Monitoring
Skills:
Unix Shell Scripting, Agile Development Methodologies, Sql Server Development, Pl Sql, Sql, Python, data quality validation, CI CD principles, Oracle databases, database security principles
Skills:
Java, Cloud Computing, Hadoop, Scala, Data Governance, Apache Airflow, Nosql, Data Management, Spark, Python, Luigi, Data warehousing principles, Data quality functions
Skills:
graph databases , object storage , Java, AWS Glue, Data Modeling, Sql, ELT, Python, Etl, column-family databases, key-value stores, IAM roles and permissions, non-relational databases
Skills:
Alteryx, Pyspark, Apache Spark, Sql, Jenkins, Git, Databricks, Azure, Python, AWS, Etl, Azure DevOps
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