About the Role
Role details below.
Responsibilities
- Design, build, and maintain cloud-native data infrastructure using Terraform for IaC.
- Develop and optimize data pipelines leveraging AWS services (Lambda, Fargate, Step Functions, S3, Kinesis, DynamoDB, Aurora, etc.) and Snowflake.
- Implement ELT workflows within dbt in partnership with our Analytics Engineering function.
- Build and maintain LLM frameworks, ensuring high-quality and cost effective outputs.
- Automate infrastructure and pipeline deployments with CI/CD best practices.
- Monitor, debug, and improve system performance with strong observability and logging practices.
- Partner with cross-functional teams (analytics, data science, product, engineering) to deliver high-quality data solutions.
- Mentor teammates and contribute to engineering standards, raising the technical bar across the team.
Requirements
- 5+ years of professional experience in data engineering or software engineering, with emphasis on scalable data systems.
- Deep experience with AWS cloud services (especially Lambda, Fargate, Step Functions, S3, DynamoDB, Aurora).
- Hands-on expertise in Terraform and/or AWS CDK for managing infrastructure as code.
- Strong knowledge of SQL and experience with Snowflake or another cloud data warehouse.
- Proficiency with dbt and modern ELT patterns.
- Solid coding skills in Python (or another general-purpose language).
- Experience building pipelines to support AI/ML workflows (feature engineering, training data pipelines, model monitoring).
- Understanding of CI/CD workflows, Git-based development, and containerization (Docker).
- Knowledge of data quality, governance, and observability best practices.
Nice to Have
- Experience in both startup and enterprise environments, with ability to adapt to fast-changing priorities while maintaining quality.
- Familiarity with orchestration frameworks (Airflow, Dagster, Prefect).
- Knowledge of streaming/event-driven architectures (Kinesis, Kafka).
- Prior experience mentoring or leading engineers.
Additional Information
- Equal Opportunity Employer: ClickUp is an Equal Opportunity Employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.
- Privacy Notice: ClickUp collects and processes personal data in accordance with applicable data protection laws. Further details available in the Global Candidate Privacy Notice and, for Philippine applicants, the Philippine Data Privacy Notice.
- Visa Sponsorship: Visa sponsorship is not available for roles outside of engineering and product. For engineering and product roles, sponsorship is not guaranteed and depends on business needs at the time.
- Fraud Alert: ClickUp Talent Acquisition will only contact via @clickup.com email or through the official careers portal. They will never request fees, payments, or sensitive personal information.
- AI Processing Notice: ClickUp may use artificial intelligence and machine learning technologies to help review and screen candidates' employment applications against role-related criteria. These tool
