Data Engineer II, CMT

• Design and architect AI-native infrastructure supporting real-time data processing for AI/ML inference, training, and continuous learning at scale
• Lead the development of semantic layers and knowledge graphs enabling intelligent query routing and context-aware data access across the organization
• Architect infrastructure for agentic AI systems with multi-agent orchestration, defining patterns and best practices for the team
• Drive GenAI-powered data quality, entity resolution, and metadata management strategies that raise the bar for data integrity

• Own end-to-end accountability for complex data products from ingestion to consumption, defining SLAs and driving adoption across stakeholders
• Lead the delivery of data products with measurable quality metrics, customer satisfaction targets, and continuous improvement mechanisms
• Design and build self-service platforms with embedded governance, lineage, and discovery — enabling teams to independently access and trust data
• Define data contracts and API standards for reliable, versioned data consumption across downstream consumers

• Architect and optimize AWS infrastructure: EC2, Lambda, S3, Redshift, EMR — balancing performance, reliability, and cost
• Design high-throughput, fault-tolerant pipelines supporting analysts, data scientists, and AI agents at global scale
• Lead implementation of CDC and event-driven architectures for sub-minute data availability with end-to-end observability
• Drive infrastructure-as-code best practices using CDK, establishing reusable patterns and deployment standards

• Mentor Data Engineer I team members, conducting code reviews and elevating engineering standards
• Own operational health of critical pipelines, driving root cause analysis and long-term prevention strategies
• Author and maintain technical design documents, influencing architectural decisions across the team
• Lead peak readiness efforts and incident response, ensuring system reliability during high-traffic events
• Drive automation initiatives that reduce operational toil and enable non-linear scaling
• 3+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with SQL
• Bachelor's degree
• 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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