The ad says“Experience building data infrastructure for AI/ML: feature stores, training pipelines, embedding pipelines, model serving, or LLM integration”
The ad says“Hands-on experience with orchestration frameworks (Airflow, Dagster, or Prefect) in production environments”
The ad says“Deep expertise in AWS cloud services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora) and infrastructure as code (Terraform and/or CDK)”
The ad says“Deep expertise in AWS cloud services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora) and infrastructure as code (Terraform and/or CDK)”
The ad says“Deep expertise in AWS cloud services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora) and infrastructure as code (Terraform and/or CDK)”
The ad says“Mastery of CI/CD, Git workflows, containerization (Docker), and deployment automation”
The ad says“Hands-on experience with orchestration frameworks (Airflow, Dagster, or Prefect) in production environments”
The ad says“Strong experience with dbt and modern ELT/ETL patterns at scale”
The ad says“Mastery of CI/CD, Git workflows, containerization (Docker), and deployment automation”
The ad says“Deep expertise in AWS cloud services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora) and infrastructure as code (Terraform and/or CDK)”
The ad says“Strong experience with dbt and modern ELT/ETL patterns at scale”
The ad says“Deep expertise in AWS cloud services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora) and infrastructure as code (Terraform and/or CDK)”
The ad says“Experience with FinOps practices and cloud cost management at scale”
The ad says“Mastery of CI/CD, Git workflows, containerization (Docker), and deployment automation”
The ad says“Deep understanding of streaming and event-driven architectures (Kinesis, Kafka, or equivalent)”
The ad says“Deep expertise in AWS cloud services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora) and infrastructure as code (Terraform and/or CDK)”
The ad says“Deep expertise in AWS cloud services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora) and infrastructure as code (Terraform and/or CDK)”
The ad says“Hands-on experience with orchestration frameworks (Airflow, Dagster, or Prefect) in production environments”
The ad says“Advanced Python skills with emphasis on building reusable libraries, frameworks, and tooling”
The ad says“Deep expertise in AWS cloud services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora) and infrastructure as code (Terraform and/or CDK)”
The ad says“Expert-level SQL and Snowflake (or equivalent cloud data warehouse) knowledge, including performance tuning and cost optimization”
The ad says“Expert-level SQL and Snowflake (or equivalent cloud data warehouse) knowledge, including performance tuning and cost optimization”
The ad says“Deep expertise in AWS cloud services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora) and infrastructure as code (Terraform and/or CDK)”
The ad says“Deep understanding of streaming and event-driven architectures (Kinesis, Kafka, or equivalent)”
The ad says“Deep expertise in AWS cloud services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora) and infrastructure as code (Terraform and/or CDK)”
Values
The ad says“Familiarity with data mesh or data product paradigms”
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
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
Benefits
16” MacBook Pro
Moving Expenses
$200/mo commuter benefits
Team lunches each week
401(k) match up to 2%
Unlimited snacks, kombucha, and cold brew
Health insurance
Dental insurance
ClickUp swag
Teammate recognition rewards
Flexible PTO
Preferred experience
This role is for someone who doesn’t just build great systems, but makes the engineers around them better
Significant professional experience in data engineering or backend/infrastructure engineering, with at least 3 years operating at a senior or staff level
Deep expertise in AWS cloud services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora) and infrastructure as code (Terraform and/or CDK)
Advanced Python skills with emphasis on building reusable libraries, frameworks, and tooling
Track record of mentoring and growing engineers, with a multiplier mindset
Experience building data infrastructure for AI/ML: feature stores, training pipelines, embedding pipelines, model serving, or LLM integration
Strong communication skills: ability to write technical RFCs, influence without authority, and translate complex trade-offs for non-technical stakeholders
Strong experience with dbt and modern ELT/ETL patterns at scale
Deep understanding of streaming and event-driven architectures (Kinesis, Kafka, or equivalent)
Proven track record of owning architecture for data platforms or large-scale distributed systems
Expert-level SQL and Snowflake (or equivalent cloud data warehouse) knowledge, including performance tuning and cost optimization
Mastery of CI/CD, Git workflows, containerization (Docker), and deployment automation
Hands-on experience with orchestration frameworks (Airflow, Dagster, or Prefect) in production environments
Unsure if you meet all the qualifications of this job description but are deeply excited about the role? We hire based on ambition, grit, and a passion for improving the way people work. If you think ClickUp is the company for you, we encourage you to apply!
Experience with FinOps practices and cloud cost management at scale
Prior experience in a technical leadership role without direct reports (staff/principal IC track)
Familiarity with data mesh or data product paradigms
Contributions to open-source data tools or technical communities
Experience operating data platforms at high scale (petabyte-level warehouses, millions of events/sec)
