Senior Data Platform Engineer

Summary

Join OpenTable's Data Engineering team as a Data Platform Engineer and contribute to a wide range of initiatives impacting diners, restaurants, and internal stakeholders. You will work on generative AI for content summarization and question answering, data pipelines providing restaurant insights, diner analytics projects powering ML, Sales, and Marketing, and integrations with partners. This remote role (initially, transitioning to hybrid) requires proven experience in Site Reliability Engineering or MLOps with a focus on data infrastructure, knowledge of data engineering technologies and principles, and proficiency in Python and Kubernetes. You will collaborate with Infrastructure SREs, Data Engineers, and the Machine Learning team to build and deploy robust solutions. OpenTable offers a competitive salary, comprehensive benefits, and the opportunity to work on impactful projects with a wealth of data.

Requirements

• Proven experience with Site Reliability Engineering or MLOps with a focus on data infrastructure
• Knowledge of the technologies and principles of data engineering
• Experience building, testing, deploying, monitoring, and maintaining production systems
• Proficient in Python, at least one strongly typed language, and Kubernetes

Responsibilities

• Generative AI for content summarization and question answering
• Data pipelines which provide insights to restaurants on their guests, revenue, and operations
• Diner analytics projects which power ML, Sales, and Marketing workstreams
• Integrations with partners to ingest and export data to support business critical partnerships
• As a Data Platform Engineer you will work closely with Infrastructure SREs, Data Engineers, and the Machine Learning team to craft and deploy robust and well governed solutions
• You will lead both on-premise and cloud based infrastructure, and be responsible for maturing our DataOps and MLOps across the organization

Preferred Qualifications

• Familiarity with our stack (PySpark, Databricks, Airflow, Python, K8s, AWS)
• Machine Learning experience (particularly MLOps, LLM Evaluation / Monitoring)
• Java proficiency
• Track record of project leadership, cross-team collaboration, and coordination with Product Managers and other stakeholders
• Pipelines: Spark, Airflow, Databricks, Snowflake, S3, Delta Lake
• ML: PyTorch, XGBoost / CatBoost, Large Language Models
• Deployment: Docker, Kubernetes, Helm, Prometheus, Graphite/Grafana
• Infrastructure: Kafka, ElasticSearch, Postgres, MongoDB, Redis, Qdrant
• Build: Flask, Gunicorn, Poetry, TeamCity, Spring, Maven

Benefits

• Paid Time Off - 20 days a year
• Birthday/celebration PTO - 1 day
• Annual company weeks off
• Flexible sick time off
• Paid volunteer time
• Parental Leave Benefits
• Dental & Vision Insurance
• Life & Disability Insurance
• Group RRSP and DPSP
• Major Medical Insurance (dependent care options)
• Annual cash bonus
• Equity grant
• Health benefits
• Flexible spending account
• Retirement benefits
• Life insurance
• Paid time off (including PTO, paid sick leave, medical leave, bereavement leave, floating holidays and paid holidays)
• Parental leave and benefits