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Active1mo ago

Staff Data Engineer

Clickup·📍 United States

Employment

FULL TIME

Work mode

On-site

Experience

SENIOR LEVEL

Salary

Not disclosed

Salary not disclosed

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Role overview

Job description

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 experienc

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Role market pulse

How Data Engineer demand looks in United States

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Posted 30d

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Remote share

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33.3%

Salary trend 1Y

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What they are looking for

Skills & requirements

Qualification

Significant professional experience in data engineering or backend/infrastructure engineering, with at least 3 years operating at a senior or staff level. Proven track record of owning architecture for data platforms or large-scale distributed systems. Deep expertise in AWS cloud services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora) and infrastructure as code (Terraform and/or CDK). Expert-level SQL and Snowflake (or equivalent cloud data warehouse) knowledge, including performance tuning and cost optimization. Strong experience with dbt and modern ELT/ETL patterns at scale. Advanced Python skills with emphasis on building reusable libraries, frameworks, and tooling. Hands-on experience with orchestration frameworks (Airflow, Dagster, or Prefect) in production environments. Experience building data infrastructure for AI/ML : feature stores, training pipelines, embedding pipelines, model serving, or LLM integration. Deep understanding of streaming and event-driven architectures (Kinesis, Kafka, or equivalent). Mastery of CI/CD, Git workflows, containerization (Docker), and deployment automation. Strong communication

Department · Growth

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Hiring company

Clickup

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