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Salary
≈ $61k – $121k per year (Estimated)
Location
Hybrid (Toronto, Canada)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 11, 2026. First seen by Alion on Sep 28, 2026. OpenTable scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Restaurant booking available 24/7: Find and book a table from the best restaurants on OpenTable UK - the restaurant reservation site trusted by 1000s of Brits to book the perfect table.

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.

Missions

  • 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.

Profil recherché

- 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

- 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

- 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

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