Data Engineer
US$130,000 – US$150,000 / yr base salary
Posted 7 May 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 5+ yrs
- Management level
- Individual contributor
- Employment
- Remote
| Base salary | US$130,000 – US$150,000 / yr |
|---|
Integration meets Innovation
At Celigo, we believe integration should empower — not exhaust — innovation. As a modern Integration and Automation Platform (iPaaS), we’re on a mission to simplify how companies integrate, automate, and optimize processes. Powered by game-changing technology like runtime AI and prebuilt, mission-critical integrations, Celigo is redefining how businesses connect their world.
Celigo is looking for a Data Engineer to contribute to the development, scaling, and maintenance of our Snowflake-based data ecosystem. You will implement and deliver scalable ELT pipelines, production-grade data models, and the observability frameworks that keep them reliable — translating business requirements into well-documented, high-performance data solutions that power analytics, BI, and ML across the organization. Partnering closely with Analytics, Product, and Engineering, you will help enforce data quality standards, align with governance practices, and continuously optimize for cost efficiency and data freshness. You'll bring strong Snowflake experience, a modern dbt-native development mindset, and a fluency with AI-assisted tooling to accelerate your own velocity and collaborate effectively with the team around you.
What would you do if hired?
- Design, build, and maintain scalable ELT/ETL pipelines and data infrastructure using Snowflake and modern tooling.
- Implement data models — including dimensional, data vault, and medallion/lakehouse patterns — to support analytics, BI, and ML use cases.
- Collaborate in Architectural discussion and decision making with team
- Collaborate with Analytics, Product, and Engineering teams to translate business requirements into reliable, well-documented data solutions.
- Establish and enforce data quality standards, automated validations, and observability frameworks to ensure high reliability across all pipelines.
- Contribute to data governance practices, including documentation, data lineage, access control, and compliance standards.
- Monitor and optimize pipeline performance, compute cost efficiency, and data freshness across the warehouse.
- Evaluate and implement emerging Snowflake features and data tooling to improve engineering velocity and reduce costs.
- Leverage AI-assisted development tools (e.g., Claude Code, GitHub Copilot, Cursor, or equivalent) to accelerate pipeline development, code review, and documentation.
Who are we looking for?
Skills & Abilities
- Strong hands-on experience with Snowflake, including performance optimization, warehouse configuration, access controls, and cost-efficient development practices.