Manager, Data Engineering

Celigo

1d•$150,000 - $175,000•Remote

About The Position

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 Manager, Data Engineering to serve as the primary architect and custodian of Celigo’s data ecosystem, balancing high-level strategic planning with hands-on technical leadership. You will own the full lifecycle of our data infrastructure—from the design of scalable ETL/ELT pipelines and cloud warehousing strategy to the enforcement of rigorous data governance and observability standards. As a bridge between technical execution and business value, you will lead a high-performing team of engineers to deliver a reliable "source of truth" that empowers Data Science, Product, and Executive leadership.

Requirements

Proven track record of managing the full project lifecycle, from initial concept and resource planning to production deployment.
Exceptional communication skills with a demonstrated ability to work cross-functionally and influence senior leadership.
Degree in Computer Science, Engineering, or a related technical field.
3+ years of technical leadership or engineering management experience, preferably in a fast-paced startup or SaaS environment.
5+ years of hands-on experience in data engineering, specifically building production-grade pipelines and distributed computing frameworks.
5+ years of experience in BI, data modeling, and modern cloud data warehousing architecture (e.g., Snowflake, BigQuery).
Advanced proficiency in SQL and at least one programming language (e.g., Python, Java, or Scala).

Responsibilities

Lead the Data Engineering department, providing technical roadmap guidance and project direction in alignment with company objectives.
Recruit, mentor, and coach a high-performing engineering team, managing performance and fostering a culture of continuous technical growth.
Oversee the end-to-end design, development, and maintenance of scalable data infrastructure, including data warehouses and robust ETL/ELT pipelines.
Partner with Data Science, Product, and Engineering teams to translate complex business requirements into effective, scalable technical solutions.
Establish and enforce data quality standards, automated validations, and observability frameworks to ensure high reliability across all pipelines.
Manage resource allocation and sprint cycles to ensure timely delivery of high-impact projects while maintaining data governance and security policies.
Evaluate and integrate emerging industry trends and tools to optimize data processing costs and engineering velocity.
Measure and report on team impact through defined KPIs, ensuring engineering output directly supports business goals.