Senior AI-First Data Engineer

Join a high-growth technology organization building an AI-native data platform that powers analytics, automation, and intelligent agents across the business. This senior role focuses on evolving the data architecture from legacy batch systems to a cloud-native, streaming-first foundation that serves both human and machine consumers. The position sits at the intersection of data engineering, AI enablement, and platform transformation.

• Lead the evolution of a cloud-native, AI-first data platform, migrating pipelines from batch to near-real-time and streaming architectures
• Build data products consumable by AI agents, analytics systems, and business users, including semantic layers and metadata management
• Improve reliability, observability, governance, and performance across the data stack while establishing engineering standards
• Use AI to accelerate development, testing, documentation, monitoring, and operational workflows
• Enable AI agents to safely query, understand, and act on business data through well-designed interfaces and guardrails
• Mentor engineers, conduct architecture reviews, and raise the technical bar across the data and analytics organization

• Senior-level experience designing and operating cloud-native data platforms at scale
• Strong hands-on skills with Databricks, dbt, Airflow, Python, and SQL
• Background building AI-ready data assets, semantic layers, and metadata-driven architectures
• Familiarity with RAG systems, vector databases, knowledge graphs, or enabling AI agents to consume operational data
• Track record of mentoring engineers and leading architecture decisions across teams
• Ability to partner effectively with Product, Engineering, GTM, and AI stakeholders

• Experience transitioning from on-premise batch systems to streaming-first infrastructure
• Background enabling self-service analytics for non-technical stakeholders without sacrificing governance

• Remote-friendly distributed team model with collaboration hubs in multiple global locations
• Environment described as AI-native, with active use of AI tooling across engineering and operations