What You'll Do
Design and manage data ingestion pipelines that handle both structured and unstructured data from multiple sources. Lead the evolution of data architecture on Databricks, ensuring systems are efficient and can scale with growing demands. Develop platform capabilities that support the full lifecycle of machine learning models—from training to deployment and monitoring in production.
Advise teams on current best practices in ML engineering and help integrate reliable, automated workflows. Take end-to-end ownership of technical initiatives, guiding them from concept through delivery. Work closely with data, product, and engineering teams to understand needs and deliver solutions that align with business goals.
Requirements
- Minimum of five years of software development experience focused on data and machine learning systems
- Strong command of SQL, Python, and Databricks for data processing and analytics
- Hands-on experience with Airflow, Kafka, and Redshift in production environments
- Solid understanding of data modeling and database design principles
- Proven ability to build, deploy, and maintain machine learning models, including language models
- Experience creating model serving pipelines for batch, streaming, and real-time inference
- Track record of operationalizing ML systems with robust CI/CD and monitoring practices
- Skilled at troubleshooting complex systems with precision and strategic thinking
- Clear communicator who can engage effectively with both technical and non-technical collaborators
Technical Stack
Core technologies include SQL, Python, Databricks, Airflow, Kafka, and Redshift. You'll work within a modern data ecosystem designed for scalability and agility.
Benefits
- Equity in the form of stock options
- TFSA/RRSP with a 4% company match
- Full medical, dental, and vision coverage for employees and dependents
- Flexible time off, company holidays, and designated focus periods
- Access to paid AI tools with minimal usage restrictions
- Enhanced parental leave top-up after six months of employment
- Life insurance and short- and long-term disability coverage
- Meals, team offsites, and customer engagement events
- Work From Anywhere Month and annual meeting-free weeks
- Hybrid work model with in-office presence on Tuesdays and Wednesdays
