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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Analytics Engineer, Data Platform - **Company:** Proper Hospitality - **Location:** Santa Monica, CA, United States - **Experience:** Experienced - **Salary:** $140,000 - $160,000 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Cloud Computing, Continuous Integration, Information Engineering, Data Hub, Data Infrastructure, Data Security, Data Sharing, Data Visualization, Software Debugging, Github, Python (Programming Language), Protel, Role-Based Access Control, Power BI, Standard Sql, Tableau (Software), Large Language Models, Snowflake, Git, Virtual Agents, Looker Analytics, Data Pipelines, Automation Anywhere - **Published:** October 16, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=9155639e76e6a19f ## About the Role Ideal Background * 3+ years of experience in data engineering, or 5+ years in data science or analytics * New grads 12 years of experience in a data or analytics role) will be considered if they demonstrate extremely strong proficiency, extraordinary tenacity, and genuine humility Required * Strong SQL and deep, hands-on experience with Snowflake, including building and operating pipelines with orchestration (tasks, streams, dynamic tables, or an external orchestrator) * Experience building data pipelines and models that others depend on Python (or a comparable language) for tooling, automation, and pipeline work * Working knowledge of Git and CI/CD, or a willingness to learn it quickly * A methodical approach to debugging: you reproduce, isolate, and find the root cause * Strong fundamentals in coding and systems design that you can demonstrate without AI assistance * Clear communication with technical and non-technical stakeholders, and the judgment to manage competing requests Nice to Have * Experience with a range of business intelligence and visualization tools (e.g., Tableau, Looker, Sigma, Power BI) * Experience with our stack: + Snowflake security and governance: RBAC design, masking policies, row-level access, and data sharing + GitHub Actions for orchestration and deployment, alongside native Snowflake orchestration + Transformation frameworks (e.g., dbt) and ingestion tools + Python services deployed on a cloud hosting platform, and infrastructure as code + Hospitality source systems: property management Infor HMS, F&B point of sale Toast, sales CRM, HR, and revenue management Experience building with LLMs, agents, AI-powered workflows, or internal data apps + Data modeling and dimensional design, plus testing and observability practices ## Description We're seeking an Analytics Engineer to join our corporate team in Los Angeles. Our warehouse and core raw pipelines are built. Your job is to keep them healthy, make them easy to use, and strengthen the foundation for AI-native work like workflows and data agents. This is an end-to-end, full-stack role focused primarily on data pipelines and foundations, with a front-row lens into how the hospitality industry runs. What You'll Do Maintain & Improve Our Pipelines (Core of the Role) * Monitor, triage, and resolve data pipeline bugs and failures, and find root causes rather than patching symptoms * Manage the intake and prioritization of data issues and requests, and keep stakeholders informed * Keep data models, tests, and documentation current so the warehouse stays trustworthy * Spot recurring failure patterns and build monitoring, alerting, and data quality checks to prevent them Build Internal Tooling & Infrastructure * Design and deploy tools and infrastructure that let teams access and work with data in our data hub * Automate repetitive operational work (backfills, access provisioning, validation, reconciliation) * Own the deployment and configuration of the supporting services behind these tools Build the Foundation for AI-Native Work * Make sure data is clean, well-modeled, secure, and documented enough to support AI workflows, data agents, ML, and advanced analytics * Partner with analysts, data scientists, and operators to productionize datasets, features, and agent-ready data * Help make AI tools usable and trustworthy for non-technical operators Support Stakeholders * Respond to data requests from Finance, Revenue, Marketing, Operations, and property teams * Translate business questions into the right data answers, and know when something needs a new model rather than a one-off query * Document institutional knowledge such as data quirks, definitions, and lineage Occasional Analytics Work * Build and maintain reports and dashboards as needed Learn the Business from the Ground Up The best data work comes from understanding the operations behind the numbers. Expect to: * Take part in site visits to our properties * Join training sessions and hands-on operator learning experiences * Spend time with the front desk, F&B, events, and revenue teams to see how the systems you support are used day to day, * First 30 days: Take ownership of the issue queue and stakeholder requests. You learn the stack, visit a property, and become the person teams go to when something looks off. * First 90 days: Help generate new, value-additive work: new datasets, analyses, or interactive data tools that give the business something it didn't have before. * First 6 months: Raise the quality of our data pipelines and make a major change to our core Snowflake platform to make it more scalable, with improvements across data security, data modeling, cost management, or rollout infrastructure. Our Interview Process We want to see how you think, so part of our process is a technical assessment completed without AI assistance. You should be able to work through a systems design discussion and a basic coding exercise on your own. We use AI heavily in our day-to-day work and expect you to as well, but strong fundamentals are what let you direct it well and catch it when it's wrong. Beyond that, expect conversations about your past work and how you approach stakeholders and ambiguity., Proper Hospitality will consider qualified applicants with criminal histories in a manner consistent with local Fair Chance Hiring Ordinances.