Responsibilities
- Define and validate the technical blueprint across cloud data warehouse, clean room infrastructure, embedding compute, and privacy controls
- Own the data modeling strategy for large-scale behavioral signals across multiple data sources and device types
- Design the embeddings architecture and feature store supporting advertising, commerce, and AI use cases
- Guide clean room design and ensure compliance with applicable privacy frameworks
- Identify and resolve critical path blockers across infrastructure, integrations, and identity resolution
- Pressure-test technical proposals against real-world scale and operational complexity
- Bridge between Blend’s engineering and data science teams and the client’s senior technical stakeholders
- Participate in regular leadership touchpoints with the client’s commercial and product leadership
- Translate technical capabilities into commercially relevant differentiation
- Ensure the technical roadmap aligns with go-to-market milestones
- Serve as a credible technical voice in early client and partner conversations
Requirements
- Enterprise data platforms (Snowflake, AWS, or equivalent)
- Real-time and batch data architecture
- ML/AI systems and embeddings infrastructure
- Data privacy frameworks and compliance-by-design approaches
- Clean rooms, DSPs, and SSPs
- You’ve worked directly with CTO-level stakeholders — not through layers
- You move comfortably between technical depth and business context
- You articulate architectural tradeoffs clearly and in terms of business impact
- You’re comfortable in high-stakes client or investor settings
- You ask hard questions about scale, cost, compliance, and risk before committing to approaches
- You hold opinions but update them when presented with better information
- You see your role as unblocking the team, not bottlenecking it
- You’ve worked in embedded delivery or partner roles
- You don’t need to own everything to drive impact
- You value getting to the right answer over being the one with the answer
