Principal Data Architect

Principal Data Architect

Reports to: SVP of Technology

Department: Research and Development

Level: Principal Individual Contributor (Player / Coach / Data Platform Architect)

Location: Remote, US.

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.

The Outcomes You Will Drive

• Unified Data Infrastructure: A single, governed data platform in Snowflake with a canonical data model that connects our product database with Salesforce, Zendesk, Outreach, and Netsuite. One source of truth that serves every function in the company.
• Federation Standards: Data contracts, modeling conventions, semantic layer governance, and quality standards that let every function move fast on the shared platform without breaking each other.
• AI Products: The data infrastructure, models, and ML capabilities to deliver Revenue Intelligence (dynamic F&B recommendations, menu insights, demand forecasting, network benchmarking) and to support the agentic products on the roadmap.
• Product Analytics: Instrumentation strategy, usage measurement, conversion funnel analytics, and the datasets the product organization needs to build and improve features with confidence.
• Business Intelligence: A trusted reporting layer serving RevOps, Finance, and Marketing with unified customer views, pipeline analytics, ARR reporting, and demand gen attribution.

What You Will Own:

Architect the Platform

• Own the end-to-end architecture for Tripleseat's data platform: Snowflake warehouse, dbt transformation layer, ingestion, orchestration, semantic layer, lineage, and governance.
• Design the canonical data model that unifies our product database with Salesforce, Zendesk, Outreach, NetSuite, and product instrumentation into a single source of truth.
• Make the foundational decisions (storage strategy, modeling approach, performance, cost, governance) that determine whether the platform scales with our AI product roadmap.
• Define the data contracts and quality standards that production AI features depend on.

Build, Not Just Direct

• Write production dbt models. Design schemas. Build pipelines. Debug performance. You spend most of your week in code.
• Deliver the data infrastructure required for Revenue Intelligence: dynamic F&B minimum recommendations, menu performance insights, demand forecasting, and network benchmarking powered by data from 20,000+ venues.
• Solve the hard data quality problems that block our AI ambitions: contact deduplication across millions of records, menu taxonomy standardization across 20,000+ venues with unstructured data, and F&B reconciliation.
• Build the trusted reporting layer that serves RevOps, Finance, and Marketing with unified customer views, pipeline analytics, ARR reporting, and demand gen attribution.

Shape and Coach the Data Team

• Help shape the data organization as it grows. Influence hiring, leveling, and how roles fit together across data engineering, analytics engineering, and data science.
• Player-coach the analytics engineers and Snowflake builders already in the organization. Run design reviews, code reviews, and architecture reviews. Set the standards. Write the playbooks others run from.
• Pair with practitioners on the hardest problems. Teach by shipping alongside them.
• Partner closely with the SVP of Technology on org design, prioritization, and how the data function evolves over the first 12 to 18 months.

Partner Cross-Functionally

• Partner with the Director of AI Products to validate data feasibility for every AI product on the roadmap, design evaluation datasets, and ensure the data infrastructure delivers what the product needs at the pace the product needs it.
• Define and execute the product instrumentation strategy by pairing up with the CPO. Rationalize how we measure product usage, conversion funnels, and feature adoption.
• Partner with the GTM analytics function in the CRO organization on shared models, definitions, and the metrics layer that everyone consumes.
• Partner with the CFO organization on the financial data model, ARR and pipeline reporting, and the GTM-to-Finance reporting layer used for board and investor reporting.
• Translate ambiguous business questions into a prioritized data roadmap. Communicate tradeoffs in plain language.

What You'll Bring:

• 10+ years of hands-on data engineering and architecture experience in growth-stage SaaS. You have personally built the platforms that power AI or ML features in production, not dashboards.
• Humble, hungry, and smart. You have high standards and strong opinions, but low ego. You build trust, listen well, and know how to push for better outcomes while bringing others along.
• Deep, current expertise in the modern data stack: Snowflake, dbt, pipeline orchestration, semantic layers, and modeling at scale. You ship code, not slideware.
• Strong opinions on data modeling (dimensional, Data Vault, wide-table, semantic layer) and the judgment to pick the right pattern for the problem in front of you.
• 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. You raise the bar through architecture, code review, and standard-setting.
• Foundational leadership instincts. You can help shape a team and a function from zero, partnering with leadership on roles, hires, and operating model, while staying hands-on as the senior practitioner.
• Strong product instinct. You make infrastructure decisions based on what the product roadmap needs, not what is architecturally elegant.
• 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 Success Looks Like in Year One:

• Canonical data model designed, documented, and adopted as the single source of truth across product, GTM, and finance.
• Snowflake and dbt architecture in production with clear standards, lineage, and cost controls.
• Revenue Intelligence shipped on a data foundation that holds up to scale and accuracy expectations.
• Data feasibility de-risked for every AI product on the roadmap before engineering commits.
• A coherent data team taking shape, with practitioners operating one level above where they started, by your direct coaching and standard-setting.

Salary Range: $220,000.00 to $240,000.00 annually

Compensation is based on a variety of factors, including relevant experience, skill set, geographic location, and alignment with our internal compensation framework. This role is also eligible for additional benefits and incentives.

Tripleseat truly values its employees and places a high emphasis on their well-being and happiness. We understand that our people are the driving force behind our success and strive to create a positive and supportive work environment. We love what we do and who we get to do it with!

Benefits are subject to change and may vary based on role and location. Here are some of the awesome benefits that Tripleseat offers to its employees: