As a Senior AI/ML Engineer, you will develop and deploy advanced AI models to enhance personalized marketing strategies and improve member engagement at Chime.
Staff Data Engineer
📅 Jun 30
Data EngineeringAWSSnowflakeSQL
📜 Description
- 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 technologies, Snowflake, and dbt.
🛠️ Requirements
- 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.
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