Data Engineer (Restaurant AI CoPilot)
- Toronto, Canada
- Mid Level
- Posted
Skills
Required
- data engineering
- Snowflake
- Kubernetes
- data architecture
- software design
- Python
- SQL
- Java
- PySpark
- Airflow
- Kafka / Delta Lake / vector/NoSQL databases
Preferred
- monitoring
- Machine Learning development
- NLP / LLMs / RAG / recommendations / MLOps
- containerization, orchestration
- Docker / Helm / Prometheus / Grafana
- ensuring scalability and reliability
Join OpenTable as a Data Engineer on the Data Science team. You will design, build, and maintain data solutions that power diner features, partner integrations, and advanced AI initiatives. Collaborate with cross-functional teams to deliver scalable data products and enhance user experiences globally. Enjoy generous benefits, including paid vacation, parental leave, and mental health support.
Responsibilities
- Design, build, and maintain robust data solutions that power diner features, partner integrations, and advanced AI initiatives.
- Collaborate with cross-functional teams to architect and govern production data services, ensuring scalability and reliability.
- Monitor and optimize production systems to ensure high performance, data availability, and system integrity.
Requirements
- Experience working in cross-functional environments and collaborating with product and technical stakeholders
- Demonstrated professional experience in data engineering principles, data architecture, and software design
Experience constructing scalable batch and streaming data pipelines
- Proficiency in Python, SQL, and at least one strongly typed language (such as Java)
- Proven track record of building, testing, deploying, monitoring, and maintaining production data systems
- Experience with data engineering stack components such as PySpark, Databricks, Snowflake, Airflow, Kubernetes, and AWS
- Familiarity with data storage and infrastructure solutions such as Kafka, Snowflake, Delta Lake, or vector/NoSQL databases
- Understanding of A/B testing best practices and data-driven product evaluation
Preferred
- Knowledge or experience in Machine Learning development (e.g., NLP, LLMs, RAG, recommendations, or MLOps)
- Familiarity with containerization, orchestration, and monitoring tools like Docker, Kubernetes, Helm, Prometheus, or Grafana
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