Senior Data Engineer

ClickUp ClickUp · Enterprise · United States · Growth

Senior Data Engineer to own the architecture and technical vision of ClickUp's AI-native data platform, focusing on building and evolving data pipelines for AI/ML workloads, including LLM frameworks, feature stores, training data systems, and model monitoring. The role involves designing scalable systems, driving cross-functional initiatives, and mentoring engineers.

What you'd actually do

  1. Own the technical architecture of ClickUp's data platform, making design decisions that balance scalability, cost, reliability, and velocity.
  2. Define and drive the technical roadmap for data infrastructure in partnership with leadership.
  3. Design systems at scale: build frameworks, abstractions, and patterns that other engineers use daily.
  4. Lead complex, cross-team technical initiatives spanning data engineering, analytics engineering, data science, and data analytics.
  5. Drive cost optimization across cloud infrastructure and compute, turning efficiency into a competitive advantage.

Skills

Required

  • AWS serverless technologies
  • Snowflake
  • dbt
  • Terraform
  • Python
  • orchestration frameworks (Airflow, Dagster, or Prefect)
  • data infrastructure for AI/ML
  • streaming and event-driven architectures
  • CI/CD
  • Git workflows
  • containerization (Docker)
  • deployment automation
  • communication skills
  • mentoring engineers

Nice to have

  • data mesh
  • data product paradigms
  • FinOps practices
  • cloud cost management at scale
  • technical leadership role without direct reports
  • contributions to open-source data tools

What the JD emphasized

  • AI fluency as part of our hiring process
  • own the architecture
  • technical vision
  • hardest engineering problems
  • set the technical bar
  • drive cross-functional alignment
  • shape how we think about reliability, scalability, cost, and developer experience
  • makes the engineers around them better
  • Own the technical architecture
  • Define and drive the technical roadmap
  • Design systems at scale
  • Lead complex, cross-team technical initiatives
  • Drive cost optimization
  • Build and evolve our data pipelines
  • Establish and champion engineering standards
  • Design and maintain infrastructure for AI/ML workloads
  • Mentor senior engineers
  • Influence org-wide technical decisions
  • Proven track record of owning architecture
  • Deep expertise in AWS cloud services
  • Expert-level SQL and Snowflake
  • Strong experience with dbt
  • Advanced Python skills
  • Hands-on experience with orchestration frameworks
  • Experience building data infrastructure for AI/ML
  • Deep understanding of streaming and event-driven architectures
  • Mastery of CI/CD, Git workflows, containerization (Docker), and deployment automation.
  • Strong communication skills
  • Track record of mentoring and growing engineers

Other signals

  • AI-native company
  • AI workspace
  • AI/ML workloads
  • LLM frameworks
  • feature pipelines
  • training data systems
  • model monitoring
  • embedding pipelines
  • model serving
  • LLM integration