About This Role
This Analytics Engineer role involves building the foundational platform to democratize data at Convene Hospitality Group (CHG), ensuring consistent and trusted answers for various stakeholders. The position focuses on owning the entire data path from ingestion to visualization, including governance and observability, and is part of the Data Platform team.
Responsibilities
- Partner with the business, including Finance, Sales, Operations, and venue teams, to understand needs and translate them into trusted models and metrics
- Own ingestion for assigned domains, setting up and maintaining Fivetran connectors, landing data in bronze, and handling schema drift and load failures
- Model the business by building dbt models that move data through bronze, silver, and gold layers, shaping gold for easy understanding and use by non-data teams
- Own the semantic layer, defining metrics, dimensions, and relationships to ensure consistent meaning across dashboards, searches, and agent answers
- Tune synonyms and descriptions for accurate model selection, trace wrong answers to root causes, and help decide where definitions reside
- Power self-service in ThoughtSpot by building models and Liveboards for data exploration, and converting user questions into new test cases
- Own the quality of conversational analytics, testing answers like code, building and maintaining a golden question set of real business questions with certified answers as test cases
- Run regression suites on every model or semantic change, blocking releases that fail, and backing models with dbt tests and clear documentation
- Apply governance daily by tagging sensitive data at ingestion, applying access controls like tag-based masking and row access policies, and following team standards
- Monitor freshness, data quality, and pipeline health to proactively address problems before they impact dashboards or agent answers
- Tune query and model performance, from incremental dbt models to warehouse sizing, to ensure fast answers and controlled Snowflake costs
- Work AI-native, leading with specs, then assigning end-to-end tasks to agents, from exploring source data to building models, tests, and documentation
- Hold agent and human work to the same review standards, ensuring code from AI and teammates receives equal scrutiny
- Share learnings and help establish the playbook for agentic data work
Requirements
- 3+ years in analytics engineering, data engineering, or BI development, building data products people rely on
- Strong SQL writing skills and experience building and maintaining dbt models in production
- Experience with a cloud data warehouse, ideally Snowflake
- Experience with ELT ingestion tools like Fivetran and ability to troubleshoot source-data issues such as schema changes, late-arriving data, and API limits
