Design and implement scalable, real-time data pipelines to move and transform customer and transaction data from multiple global sources.
Architect resilient data systems that ensure reliability, observability, and data integrity across distributed environments.
Collaborate with AI and product teams to structure and prepare data for intelligent features like recommendation systems, insights generation, and predictive analytics.
Champion event-driven architectures, supporting seamless data ingestion from POS systems, APIs, and third-party integrations.
Define best practices for data governance, schema evolution, and real-time monitoring.
Mentor and guide team members, fostering growth and sharing knowledge across the engineering organization.
Requirements
Extensive experience building and scaling data architectures that handle diverse global data sources.
Proven background in real-time data processing, leveraging tools like Kafka, Pub/Sub, and ClickHouse.
Proficiency in TypeScript and experience working across full-stack environments.
Strong understanding of SQL and NoSQL databases, with expertise in schema design, performance tuning, and data modeling.
Familiarity with ETL/ELT frameworks (e.g., dbt, Airflow, Dagster) and cloud platforms like AWS and GCP.
Experience with Vercel is a plus.
Experience empowering AI systems through structured, high-quality data (e.g., embeddings, vector databases, RAG pipelines).
Strong grasp of event-driven software patterns and distributed system fundamentals.
An interest in mentorship and helping elevate others on the team.
Benefits
Personal or family health insurance options
Generous annual stipend for work equipment and hardware
Unlimited vacation with a minimum required use per year
RRSP matching
Competitive compensation and flexible remote work culture
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