Senior Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of the technical architecture for ClickUp's data platform, making design choices that ensure a balance of scalability, cost, reliability, and speed.

• Define and lead the technical roadmap for data infrastructure in collaboration with leadership.

• Create scalable systems: develop frameworks, abstractions, and patterns for daily use by other engineers.

• Spearhead complex, cross-team technical projects involving data engineering, analytics engineering, data science, and data analytics.

• Promote cost efficiency across cloud infrastructure and compute, transforming efficiency into a competitive edge.

• Develop and enhance our data pipelines utilizing AWS serverless technologies (Lambda, Fargate, Step Functions, Kinesis, S3, DynamoDB, Aurora), Snowflake, and dbt.

• Establish and advocate for engineering standards, including observability, testing, CI/CD, code reviews, and documentation practices.

• Design and maintain infrastructure for AI/ML workloads, encompassing LLM frameworks, feature pipelines, training data systems, and model monitoring.

• Mentor senior engineers, offering technical guidance through design reviews, and elevate the overall engineering quality of the team.

• Influence technical decisions across the organization and represent data engineering in discussions concerning company-wide architecture.

⛳️ Requirements

• Extensive professional experience in data engineering or backend/infrastructure engineering, with a minimum of 3 years in a senior or staff role.

• Proven success in managing architecture for data platforms or large-scale distributed systems.

• In-depth knowledge of AWS cloud services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora) and infrastructure as code (Terraform and/or CDK).

• Expert-level proficiency in SQL and Snowflake (or a comparable cloud data warehouse), including performance optimization and cost management.

• Strong expertise in dbt and modern ELT/ETL methodologies at scale.

• Advanced Python capabilities focused on creating reusable libraries, frameworks, and tools.

• Practical experience with orchestration frameworks (Airflow, Dagster, or Prefect) in production settings.

• Experience in developing data infrastructure for AI/ML, including feature stores, training pipelines, embedding pipelines, model serving, or LLM integration.

• Comprehensive understanding of streaming and event-driven architectures (Kinesis, Kafka, or similar).

• Proficient in CI/CD, Git workflows, containerization (Docker), and deployment automation.

• Excellent communication skills: ability to draft technical RFCs, influence without formal authority, and clarify complex trade-offs for non-technical stakeholders.

• Proven history of mentoring and developing engineers with a mindset for growth.

🏝️ Benefits

• Equity

• 401k

• Health, Dental, and Vision insurance

• Spending accounts

• Life & Disability

• Paid parental leave

• Flexible paid time off

• Enhanced employee assistance program

• Employee wellness stipend

• Professional development stipend