DataEngineer

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