Staff Data Engineer

pofft Technology Inc.; Canada; Remote; CAD 150,000 - 210,000; Full time

Job summary

ClickUp is seeking a Staff Data Engineer to own the architecture and technical vision of our data platform in a remote setting. You will set the technical bar, drive cross-functional alignment on data infrastructure strategy, and solve hard engineering problems across AWS serverless, Snowflake, dbt, and Terraform.

This role emphasizes building scalable pipelines, optimizing costs, and mentoring engineers while shaping reliability and developer experience at the platform level.

Qualifications

• Significant professional experience in data engineering or backend/infrastructure engineering at senior level.
• Proven track record of owning architecture for data platforms or large-scale distributed systems.
• Deep expertise in AWS cloud services and infrastructure as code (Terraform/CDK).
• Expert-level SQL and Snowflake knowledge with performance tuning and cost optimization.
• Strong experience with dbt and modern ELT/ETL patterns at scale.
• Advanced Python skills and hands-on orchestration (Airflow, Dagster, or Prefect).
• Experience building data infrastructure for AI/ML workloads.

Responsibilities

• Own the technical architecture of the data platform, balancing scalability, cost, reliability, and velocity.
• Define and drive the technical roadmap for data infrastructure in partnership with leadership.
• Design systems at scale with frameworks, abstractions, and patterns used by engineers daily.
• Lead cross-team technical initiatives spanning data engineering, analytics, data science, and analytics.
• Drive cost optimization across cloud infrastructure and compute to gain competitive advantage.
• Build and evolve data pipelines using AWS serverless, Snowflake, and dbt.
• Establish and champion engineering standards: observability, testing, CI/CD, code review, docs.
• Mentor senior engineers and influence company-wide data decisions.

Skills

Data engineering

Architecture ownership

Python

SQL

ETL/ELT

Airflow

Dagster

Prefect

Data infrastructure

AI/ML data pipelines

Tools

AWS

Snowflake

dbt

Terraform

Job description

Staff Data Engineer Remote 1 gün 8 saat 25 dakika önce yayınlandı. Jobicy -

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.

Qualifications:

• 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.

Location

Remote