Analytics Engineer

Proper Hospitality LLC•Santa Monica, CA

40d•$155,000 - $185,000

About The Position

Proper Hospitality is seeking a visionary Analytics Engineer to help build the future of data across our growing portfolio. You will be the foundational data architect for Proper’s next-generation hospitality intelligence platform, joining as the founding member of the data engineering team. Your mission is to design, build, and own the semantic modeling layer, identity-resolution framework, and core data infrastructure that powers analytics, personalization, membership logic, and AI-driven operations across all Proper properties. This is a hands-on role with direct ownership of data modeling, governance, and data quality, with influence over technical direction, vendor management, and cross-functional alignment. You will collaborate with data engineering vendors, AI/ML engineering vendors and internal business leaders across operations, marketing, revenue management and sales to ensure our data infrastructure is accurate, scalable, governed, and actionable. You will be responsible for portfolio-wide hotel performance analytics, trend identification, and decision-support for Operations, Finance, Revenue Management, and senior executives.

Requirements

4–7+ years of hands-on experience in analytics engineering, data engineering, or modern data stack architecture
Expert-level SQL
Deep experience with dbt, dimensional modeling, and analytics engineering best practices
Strong understanding of cloud data warehouses (Snowflake, BigQuery, or Databricks)
Experience building and validating ETL/ELT pipelines and working with raw staging layers
Strong understanding of data quality frameworks, testing, lineage, and documentation
Demonstrated ability to unify data across disparate systems and design customer 360 profiles
Proven ability to translate raw data into actionable insights for operators, leaders, and executives
Ownership mentality; strong opinions about modeling quality and data integrity
Able to push back on, manage vendors and enforce standards
Comfortable designing from scratch without existing documentation
Communicates clearly with both technical and non-technical partners
Bias toward simplicity, clarity, and correctness
High degree of professional maturity and judgment

Nice To Haves

Experience in hospitality, retail, wellness, or membership-based businesses
Familiarity with reverse-ETL tools (Hightouch, Census)
Experience with event streaming (Kafka, Pub/Sub) and real-time architecture
Exposure to Python for data modeling or feature engineering
Understanding of marketing automation platforms (Klaviyo, Salesforce, Braze)
Strong data privacy and governance understanding (GDPR/CCPA)

Responsibilities

Design and own the company-wide dimensional modeling strategy using dbt (data build tool)
Create and maintain clean, well-documented, version-controlled models for core domains (PMS, POS, spa/wellness, membership, digital, etc)
Establish and enforce naming conventions, data contracts, lineage, and schema governance
Architect and maintain the Proper guest identity graph, unifying data across all systems into a single, accurate guest profile
Develop deterministic and heuristic matching rules; iterate on feature extraction, merging logic, and identity quality metrics
Implement robust data validation, monitoring, and alerting frameworks to ensure completeness, accuracy, and timeliness across all pipelines
Partner with contractors to ensure staging layers ingest data consistently and reliably
Define and maintain authoritative metric definitions (LTV, ADR, occupancy, conversion, channel attribution, membership value, churn)
Build accessible data marts and semantic layers that can serve BI tools, CRM systems, and AI services
Design metrics and data visualizations with dashboarding tools like Tableau, Sigma, and Mode
Work closely with operations, revenue management, marketing, and the executive team to understand data needs and translate them into scalable models
Provide technical guidance and enforce standards with third-party engineering vendors
Be a cross-functional champion at upholding high data integrity standards to increase reusability, readability and standardization
Build recurring analytical frameworks and dashboards for property-level and portfolio-level insights (occupancy, ADR, RevPAR, segmentation mix, pickup behavior, channel performance, cost-per-room, labor productivity, F&B covers, check averages, menu engineering)
Detect structural trends and operational inefficiencies by analyzing PMS, POS, labor, spa, digital, and membership datasets
Partner with property and cluster leadership to interpret trends, validate root causes, and tie data outputs to operational actions
Build forecasting models for occupancy, F&B demand, spa utilization, labor, and revenue
Produce executive-level performance briefs that combine data engineering rigor with applied hospitality interpretation
Create and maintain feature tables for predictive models (propensity, demand forecasting, churn, LTV)
Support experimentation and real-time personalization use cases by providing clean features and stable data sources
Maintain comprehensive documentation of all datasets, lineage, assumptions, and transformations
Own data governance, security, privacy compliance, and access controls in coordination with leadership