Key skills
Data EngineeringETL/ELT PipelinesCloud Data WarehousingData ModelingSQLPythonJavaScalaDistributed Computing FrameworksData GovernanceData Quality StandardsData Observability FrameworksETLELTData WarehousingBISnowflakeBigQuerySaaSLeadershipResource PlanningCommunication
About this role
Celigo is a modern Integration and Automation Platform (iPaaS) on a mission to simplify how companies integrate, automate, and optimize processes. The Manager, Data Engineering will lead the data engineering department, overseeing the design and maintenance of scalable data infrastructure while managing a high-performing team to ensure data governance and quality standards are met.
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
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)