Convene Hospitality Group - Data Platform Lead

• Own the data platform end to end. Architecture, reliability, and roadmap from source to decision across Snowflake, dbt, and Fivetran. Move platform configuration from the UI into Terraform, in coordination with Cloud Infrastructure, so warehouses, roles, grants and connectors are versioned, reviewed and reproducible. • Own the data platform end to end. • Rethink how we model the business. Move us from source-shaped marts to domain-oriented models built around how CHG runs. Set the modeling standards, naming conventions and review practices the team builds on. • Rethink how we model the business. • Work backward from the business question. Partner with Finance, Sales, Operations and venue leadership to turn the questions they need answered into models, metrics and definitions they trust. • Work backward from the business question. • Partner closely with product engineering. Work with product squads on schema design, data contracts, and upstream changes, so the platform and products evolve together. • Partner closely with product engineering. • Own data quality and observability. Set the testing standards, contracts, and reconciliation checks that make our numbers trustworthy, and alert an owner before a stakeholder finds a broken dashboard. • Own data quality and observability. • Own the metrics and BI layer. Roll out our BI tool and build the semantic layer behind governed dashboards in Snowflake semantic views, with certified metrics and shared definitions, so a number means the same thing everywhere it shows up. • Own the metrics and BI layer. • Bring conversational analytics online, safely. Stand up natural-language querying and agents on Snowflake’s native tools, with the evals and guardrails that keep agent, dashboard, and human answers in sync. • Bring conversational analytics online, safely. • Govern the data. Access control, PII handling and accessible documentation across analytics and AI. • Govern the data. • Lead and grow analytics engineering. Manage and hire our analytics engineers, and direct the contractors we work with today. Coach through code review, pairing, and clear expectations. • Lead and grow analytics engineering. • Keep your hands on the keyboard. Write dbt models, review PRs, debug pipelines and prototype new approaches. Expect to build a lot, especially early on. • Keep your hands on the keyboard. • What We Look For: • What We Look For: • You have 7+ years in data engineering, analytics engineering or data architecture, including building a modern data platform that people rely on in production. • You use AI agents for real multi-step work: building models, writing tests, debugging pipelines and documenting what exists. You write clear specs, give agents the right context, and verify what they produce against the real system. • You're deep on dbt and Snowflake. You've designed project structure, testing strategy and warehouse performance at scale, and you manage the platform as code with Terraform or similar. • You’re fluent in data modeling and have moved a team from source-shaped models to business-shaped, domain-oriented marts, then seen the change through to adoption. • You've built data quality and observability practices: tests, contracts, freshness monitoring and alerting that people trust. • You've built a semantic layer and governed metrics that people trust, and you understand what it takes to make natural-language and agent-driven analytics accurate. • You've worked with managed ingestion like Fivetran and know where it fits and where it breaks. • You've led beyond your own work: as a tech lead on a multi-person project, mentoring engineers, running interview loops, or directing contractors or vendors. • You explain clearly to engineers and non-engineers. You can walk an analyst through a modeling decision and a CFO through a metric definition. • You're high agency. You set direction without waiting for a spec, make architecture calls, and write down your reasoning.