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FBA is seeking a Data Engineer to help 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 supporting next-generation intelligent data platforms, this role is for you.
Core Responsibilities:
AI-Native Infrastructure & Real-Time Processing
Support the development of AI-native infrastructure for real-time data processing supporting AI/ML inference, training, and continuous learning
Contribute to building semantic layers and knowledge graphs that enable intelligent query routing and context-aware data access
Assist in developing infrastructure components for agentic AI systems with multi-agent orchestration
Implement GenAI-powered data quality checks, entity resolution pipelines, and metadata management workflows
Data-as-a-Product Delivery
Contribute to end-to-end data product delivery from ingestion to consumption
Support data products with clear SLAs, quality metrics, and customer satisfaction measures
Help build self-service platforms with embedded governance, lineage, and discovery
Implement data contracts and APIs for reliable, versioned data consumption
AWS Infrastructure & Pipeline Engineering
Work with AWS resources: EC2, Lambda, S3, Redshift, Kinesis, EMR, SageMaker, Bedrock, Neptune
Build and maintain 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
3+ years in data engineering with cloud-native architectures
Working knowledge of AWS services (Redshift, S3, Glue, Kinesis, EMR)
Experience with real-time streaming technologies (Kafka, Kinesis, or Flink)
Exposure to AI/ML infrastructure (SageMaker, Bedrock)
Proficiency in Python, SQL, and familiarity with 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
Help build the foundational infrastructure powering next-generation AI-enabled data products at Amazon FBA.
- 1+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, KornShell)
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
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: 149159435
Skills:
snowflake , Java, BigQuery, Hadoop, Scala, AWS Glue, Kafka, Redshift, Sql, Apache Airflow, Hive, Gcp, Presto, Spark, Databricks, DataFlow, Azure, Python, AWS, Luigi, Prefect, OpenSearch
Skills:
RDS, Pyspark, AWS Glue, Dynamodb, Emr, Sql, Lambda, Cloudwatch, Iam, Sqs, Sns, Python, AWS, Lake Formation, CloudTrail
Skills:
Power Bi, Adf, Pyspark, Sql, Streaming, Terraform, vector search, cdc, Feature Store, MLflow, CI CD, Unity Catalog, Synapse, ADLS, DLT Workflows, RAG, Microsoft Azure Databricks, Azure data services, Databricks Delta
Skills:
Spark SQL, Github, Pyspark, Bash, Git, Linux, Iam, Databricks, Python, AWS, Redshift Serverless, CI CD, Unity Catalog, rbac
Skills:
Azure Data Factory, SQL Server, Databricks, SSIS, Azure DevOps, MS Fabric, CI CD pipelines, Synapse Analytics, ADLS Gen2
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