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Tripleseat is the platform that more than 20,000 hospitality businesses use to manage group sales, banquets, catering, and event operations. We have the deepest proprietary dataset in hospitality event management: millions of events, granular F&B line items, conversion funnels, and booking patterns across every major US metro. This data is the foundation of our AI product strategy and the core of our competitive moat. We need a leader to build the data platform that turns it into intelligence. This is a foundational leadership role in a federated data operating model. You will help build and guide the organization's first true data strategy. Analytics ownership lives with the business functions that depend on it (GTM analytics in the Sales organization, Finance analytics in Finance, and so on). You will own the end-to-end data strategy spanning platform infrastructure, analytics, and the data science capabilities that power our AI product suite. You will be the technical authority for our data platform, the architect of our canonical model, and the player-coach who raises the bar for every data practitioner at Tripleseat. You own the canonical data model, the data contracts, and the standards that hold the federation together. You are the connective tissue. You will personally architect the Snowflake warehouse, design the canonical model, write the dbt foundations, and ship the data infrastructure that powers Revenue Intelligence, our most data-intensive product. In parallel, you will partner with our existing analytics engineers and Snowflake builders to elevate their work and shape the data team as it grows.
Job Responsibility:
Architect the Platform
Own the end-to-end architecture for Tripleseat's data platform
Design the canonical data model
Make the foundational decisions (storage strategy, modeling approach, performance, cost, governance)
Define the data contracts and quality standards
Build, Not Just Direct
Write production dbt models
Deliver the data infrastructure required for Revenue Intelligence
Solve the hard data quality problems
Build the trusted reporting layer
Shape and Coach the Data Team
Help shape the data organization as it grows
Player-coach the analytics engineers and Snowflake builders
Partner closely with the SVP of Technology
Partner Cross-Functionally
Partner with the Director of AI Products
Define and execute the product instrumentation strategy
Partner with the GTM analytics function
Partner with the CFO organization
Translate ambiguous business questions into a prioritized data roadmap
Requirements:
10+ years of hands-on data engineering and architecture experience in growth-stage SaaS
Deep, current expertise in the modern data stack: Snowflake, dbt, pipeline orchestration, semantic layers, and modeling at scale
Strong opinions on data modeling (dimensional, Data Vault, wide-table, semantic layer) and the judgment to pick the right pattern
Direct experience with the data problems that gate AI products: entity resolution, taxonomy normalization, evaluation dataset design, model monitoring, and data quality at scale
Track record of mentoring analytics engineers, data engineers, and analysts to higher levels of capability
Foundational leadership instincts
Strong product instinct
Track record of partnering cross-functionally with product, engineering, finance, and go-to-market in a centralized data model where you serve multiple internal customers
What we offer:
Competitive Medical, Dental, and Vision Insurance
Company Paid Life Insurance, Short- and Long-Term Disability Plans