Senior Product Design Manager

What you'll do

Lead the dbt product design team

• Manage and coach a team of product designers who work across dbt platform and CLI-based products.
• Designers own the full design process from problem definition and research to UX/UI and partnering with eng/PM through delivery.
• Build a culture where designers feel supported, challenged, and empowered to do thoughtful, high-quality work for deeply technical users.
• Set clear expectations, give actionable feedback, support career growth, and create the conditions for strong design craft.

Own UX strategy for dbt

• Define and drive UX strategy across dbt’s product experience.
• Identify the highest-impact experience opportunities, connect design priorities to product outcomes, and partner with Product and Engineering leadership as a strategic peer in roadmap and product direction conversations.

Provide design direction for technical data products

• Set direction for design work across complex workflows used by technical practitioners.
• Need enough technical fluency to understand the domain, evaluate tradeoffs, and partner credibly with engineering leaders.
• Be comfortable discussing data workflows, ELT, analytics engineering, developer tools, and infrastructure-oriented product experiences.

Shape AI and agentic product experiences

• Lead design strategy for AI-powered and agentic experiences within dbt.
• Design systems that make AI assistance understandable, useful, and safe for high-stakes technical work.
• Think about how product surfaces need to work for both human and AI agent personas interacting with the same data infrastructure.

Help integrate Fivetran and dbt Labs design

• Co-create a unified product experience and design culture.
• Partner with the Director of Product Design to merge systems, processes, and culture.
• Help designers navigate a new organizational context, build strong cross-functional relationships, and create clarity during a period of product and company evolution.

Build an AI-native design operating model

• Operationalize AI across the design lifecycle (from research synthesis and ideation to prototyping, documentation, and design QA).
• Establish shared workflows, quality standards, and review practices that help the team move faster without compromising product quality or consistency.
• Define cross-functional standards for when AI-generated work requires design review, ensuring clear expectations for human oversight, quality, and continuous improvement.

What we're looking for

Required experience

• 8+ years of product design experience and at least 5 years managing product designers.
• Strong people management skills, including coaching, performance development, direct feedback, and team culture building.
• Strong cross-functional leadership with Product, Engineering, Research, Data, Marketing, and executive stakeholders.
• Deep care for craft, with a leadership style focused on direction, critique, strategy, and coaching rather than acting as the primary IC designer.
• Designing for, or leading teams that design for, technically complex products such as ELT, data infrastructure, analytics engineering, developer tools, cloud platforms, data governance, observability, or adjacent enterprise infrastructure products.
• Designing AI-powered or agentic product experiences. Understand the difference between a lightweight AI feature, a copilot, and an agentic workflow.
• Experience operationalizing AI workflows for product design teams that goes way beyond AI prototyping. Defined how designers use AI across the design lifecycle and have established the workflows, standards, review practices, and quality thresholds needed to make AI-assisted work effective at team scale.
• Owning UX strategy for a meaningful product area. Can show how your design strategy influenced product direction, not just how your team delivered screens.
• Strong technical fluency. Can reason about complex systems, understand engineering constraints, and discuss tradeoffs with Product and Engineering partners.
• Experience designing for expert technical users such as data engineers, analytics engineers, software engineers, platform teams, or security teams.