Staff Data Engineer

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process.

Join us and help redefine what's possible. We're looking for a Staff Data Engineer to own the architecture and technical vision of our data platform. This is a high-leverage, high-autonomy role where you'll set the technical bar for the team, drive cross-functional alignment on data infrastructure strategy, and solve our hardest engineering problems.

You'll operate across AWS serverless technologies, Snowflake, dbt, and Terraform, but your impact goes well beyond any single tool: you'll shape how we think about reliability, scalability, cost, and developer experience at the platform level. This role is for someone who doesn't just build great systems, but makes the engineers around them better

The role

• Own the technical architecture of ClickUp's data platform, making design decisions that balance scalability, cost, reliability, and velocity.
• Define and drive the technical roadmap for data infrastructure in partnership with leadership.
• Design systems at scale: build frameworks, abstractions, and patterns that other engineers use daily.
• Lead complex, cross-team technical initiatives spanning data engineering, analytics engineering, data science, and data analytics.
• Drive cost optimization across cloud infrastructure and compute, turning efficiency into a competitive advantage.
• Build and evolve our data pipelines using AWS serverless (Lambda, Fargate, Step Functions, Kinesis, S3, DynamoDB, Aurora), Snowflake, and dbt.
• Establish and champion engineering standards: observability, testing, CI/CD, code review, and documentation practices.
• Design and maintain infrastructure for AI/ML workloads, including LLM frameworks, feature pipelines, training data systems, and model monitoring.
• Mentor senior engineers, provide technical guidance through design reviews, and raise the overall engineering quality of the team.
• Influence org-wide technical decisions and represent data engineering in company-level architecture discussions