Engineering Manager, Data AI & Analytics
Role Overview
Leads a team of Data Engineers while remaining hands-on in scalable, high-quality data delivery.
Supports global digital transformation and trusted data across Agriculture, Manufacturing, and Commercial domains.
Works with data architects, analytics teams, and business stakeholders to enable enterprise data-driven decisions.
Key Skills for This Role
Full Job Posting
Role overview
Leads a team of Data Engineers while remaining hands-on in scalable, high-quality data delivery.
Supports global digital transformation and trusted data across Agriculture, Manufacturing, and Commercial domains.
Works with data architects, analytics teams, and business stakeholders to enable enterprise data-driven decisions.
Key responsibilities
- Lead enterprise data pipeline and asset design, development, and implementation.
- Own ingestion and delivery, including architecture, maintenance, and infrastructure support; ensure efficient ELT.
- Guide engineers, conduct code reviews, mentor the team, and promote best practices.
- Partner on data models, schemas, and database design; translate stakeholder needs into solutions.
- Set documentation standards and drive automation, CI/CD, DevOps, and platform improvements.
Required qualifications
- Bachelor’s degree or higher in Computer Science, Engineering, or a related field.
- Proven end-to-end data engineering delivery experience.
- Proficiency in one or more of Python, SQL, Java, Scala, Spark, or PySpark.
- Experience with modern data platforms and a cloud platform; strong data modeling, database design, and warehousing knowledge.
- Experience leading or managing agile software development teams.
Preferred qualifications
- Advanced degree, cloud certifications, DevOps/CI-CD experience, AI/ML exposure, and significant leadership experience are preferred.
Compensation
- Target compensation is CAD 102,700–137,000 annually, plus bonus eligibility.
Team
Leads Data Engineers in the Global Data, AI & Analytics organization, partnering with Platform Engineering, Data Architecture, Analytics, and Digital Product teams.
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