Senior Data Engineer (AI/ML)
OpenTable
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What data roles keep asking for: AWS (25%), SQL (23%), Python (22%), Machine learning (12%) — counted across their open postings here.
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Preparing for this interview
Interviews for data roles keep coming back to AWS, SQL, Python, Machine learning. Practise those questions before you sit with OpenTable.
Questions you are likely to be asked
- Why do you want to join OpenTable?
- What is your experience with LLMs? Tell me one thing you learned the hard way.
- Walk me through a model you built, from the data to how it was used.
- How did you know your model was actually good, and not just good on your test set?
- Tell me about a time the data was messy or wrong. What did you do?
Prep Sarthi gives you a free mock interview: an AI interviewer asks you questions like these out loud, from your own CV and this job, and shows your score and your weakest answer.
Practise the Senior Data Engineer (AI/ML) at OpenTable interview free →This role is 100% remote across India location
About OpenTable
With millions of diners, 70,000+ restaurant partners and 25+ years of experience, OpenTable, part of Booking Holdings, Inc. (NASDAQ: BKNG), is an industry leader with a passion for helping restaurants thrive. Our world-class technology empowers restaurants to focus on what matters most – their team, their guests, and their bottom line – while enabling diners to discover and book the perfect restaurant for every occasion.
Every employee at OpenTable has a tangible impact on what we do and how we do it. You’ll also be part of a global team and its portfolio of metasearch brands. Hospitality is all about taking care of others, and it defines our culture.
About Role
We are looking for a Senior Data Engineer – AI/ML to help build the data and AI infrastructure powering our next generation of intelligent products and experiences.
This role combines modern data engineering with Generative AI. You will design scalable data platforms and pipelines while building production-grade solutions using LLMs, RAG, embeddings, vector search, and AI agents. You will work closely with data scientists, ML engineers, software engineers, and product teams to turn AI capabilities into reliable, scalable production systems.
What You'll Do
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Design and build AI/LLM data pipelines supporting training, inference, evaluation, embeddings, and retrieval workloads.
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Build production-grade RAG systems, including ingestion, chunking, embedding generation, indexing, retrieval, reranking, and context construction.
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Develop AI applications using LLMs, structured outputs, function/tool calling, and agentic workflows.
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Build and optimize semantic search and vector retrieval systems.
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Develop frameworks for LLM evaluation, monitoring, tracing, quality measurement, latency, and cost optimization.
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Design scalable batch and streaming pipelines using Databricks, Apache Spark, Delta Lake, Snowflake, and Airflow.
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Build data products and platforms that make structured and unstructured enterprise data accessible to AI applications.
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Develop reliable ETL/ELT pipelines and optimize large-scale distributed workloads for performance and cost.
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Establish data quality, governance, lineage, security, and observability practices.
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Partner with ML and application engineering teams to move AI prototypes into production-ready systems.
Required Qualifications
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5+ years of experience in data engineering, software engineering, distributed systems, or a related field.
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Strong programming skills in Python and/or Scala/Java and advanced SQL.
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Hands-on experience with Databricks, Snowflake, Apache Spark, Delta Lake, and Airflow.
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Strong experience with cloud data platforms such as Snowflake and/or Databricks.
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Practical experience building applications using LLMs or Generative AI.
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Strong understanding of RAG architectures, embeddings, vector databases, semantic search, and retrieval systems.
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Familiarity with LLM concepts including prompting, structured outputs, tool calling, and model evaluation.
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Experience designing scalable, reliable, and observable production data systems.
Preferred Qualifications
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Deep experience designing large-scale data platforms, distributed processing systems, and complex data workflows.
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Strong experience with real-time and streaming data architectures, including Kafka, Spark Structured Streaming, or similar technologies.
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Experience building low-latency data pipelines and event-driven architectures.
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Experience designing complex multi-stage ETL/ELT and data orchestration workflows using Airflow or similar platforms.
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Experience optimizing Spark/Databricks workloads, including partitioning, clustering, caching, joins, and compute optimization.
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Experience building data platforms supporting both batch and real-time AI/ML workloads.
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Experience with LLM and AI evaluation frameworks, including automated evaluations, offline/online evaluation, quality metrics, and experimentation.
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Experience building evaluation datasets and pipelines for measuring LLM/RAG/agent quality, accuracy, relevance, latency, and cost.
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Experience with AI observability and tracing, including token usage, model performance, latency, failures, and production monitoring.
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Experience with LangGraph, LangChain, LlamaIndex, or similar AI orchestration frameworks.
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Experience with vector databases such as Qdrant, Pinecone, Weaviate, or Databricks Vector Search.
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Experience with Kafka, MLflow, Unity Catalog, Databricks Mosaic AI, or model-serving platforms.
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Experience building data quality, lineage, governance, and data/AI observability frameworks.
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Strong understanding of distributed systems, cloud architecture, APIs, CI/CD, and production operations.
Impact
You will help build the data and AI foundation for intelligent products, combining large-scale data engineering, streaming systems, and modern Generative AI to deliver reliable, scalable, measurable, and production-ready AI systems.
Benefits
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Work from (almost) anywhere for up to 20 days per year
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Focus on mental health and well-being:
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Company-paid therapy sessions through SpringHealth
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Company-paid subscription to Headspace
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Annual company-wide week off a year - the whole team fully recharges (and returns without a pile-up of work!)
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Paid parental leave
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Generous paid vacation + time off for your birthday
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Paid volunteer time
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Focus on your career growth:
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Development Dollars
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Leadership development
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Access to thousands of on-demand e-learnings
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Travel Discounts
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Employee Resource Groups
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Quarterly team offsites
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Tax optimisation options
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Generous health insurance
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Pension fund
Work Environment & Flexibility
At OpenTable, we pride ourselves on fostering a global and dynamic work environment. As a team member with us, you will benefit from a schedule tailored to accommodate a global workforce operating across multiple time zones. While the majority of your responsibilities may align with conventional business hours, there will be instances where you are expected to manage communications - via calls, Slack messages, or emails - outside of regular working hours to effectively collaborate with international colleagues, respond to restaurant partners, and/or address urgent matters. OpenTable will always abide by and consider local laws and regulations.
Inclusion
We’re committed to creating a workplace where everyone feels they belong and can thrive. We know the best ideas come when we bring different voices to the table, so we're building a team as dynamic as the diners and restaurants we serve—and fostering a culture where everyone feels welcome to be themselves.
If you need accommodations during the application or interview process, or on the job, we’re here to support you. Please reach out to your recruiter to request any accommodations.
#LI-Remote #LI-MK1
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Listed on greenhouse · posted 2026-09-18. ApplySarthi collects openings and links to application pages; the role is advertised by OpenTable, not by us.