Senior Data Engineer
| Company | Mejuri |
|---|---|
| Location | Toronto, ON, Canada |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | |
| Experience Level | Senior |
Requirements
- Strong experience with Python for data engineering and building pipelines using modern orchestration tools (e.g., Dagster, Airflow)
- Proficient in ELT/ETL development with cloud warehouses like BigQuery
- Hands-on experience with DBT, version control (GitHub), and infrastructure tools such as Docker, Terraform, or Kubernetes
- Ability to build high-performance, scalable data systems that support both batch and real-time use cases
- Excellent communication skills and a collaborative approach to problem solving
Responsibilities
- Design and build scalable, reliable data pipelines using Dagster and Python
- Manage end-to-end ingestion, transformation, and delivery of data across domains, including customer, transactional, operational, and event data
- Own and evolve foundational systems like customer 360, event tracking pipelines, and data models that support marketing attribution, personalization, and analytics use cases
- Collaborate with data scientists, analytics engineers, and business teams to understand data needs and deliver performant, trusted, and production-ready data products
- Implement best practices for testing, CI/CD, observability, and infrastructure-as-code (e.g., Terraform, Docker)
- Ensure pipelines are robust, monitored, and well-documented
Preferred Qualifications
- Experience building ML or feature engineering pipelines in partnership with data science teams
- Familiarity with real-time data streaming tools such as Kafka or Spark
- Experience working in a modern marketing tech stack (e.g., Segment, Braze, CDPs)
- Exposure to experimentation frameworks or data products supporting A/B testing
- Understanding of Retail and Direct-to-Consumer workflows, challenges, and business requirements