Note: The job is a remote job and is open to candidates in USA. Elios AI is hiring a GTM Data Analyst to build a trusted reporting layer for go-to-market performance. The role will unify CRM, forecasting, and ERP data in Snowflake, define canonical GTM metrics, establish data quality processes, and deliver dashboards and narratives for Sales, Marketing, Finance, and FP&A.
Responsibilities
- Shape the GTM dimensional models in Snowflake, translating reporting needs into facts and dimensions built on CRM, forecasting, and ERP sources
- Work inside an existing medallion architecture alongside the team that owns the broader platform
- Define the canonical set of GTM metrics, so pipeline coverage, SQO, and net revenue retention mean the same thing to a rep and to the CFO
- Use AI tooling such as Claude Code as your default way of querying, modeling, and documenting, not as an occasional experiment
- Build the data quality checks and reconciliation processes that catch anomalies before anyone sees them on a dashboard
- Chase root causes upstream with the RevOps and finance owners of the source systems rather than patching the symptom downstream
- Turn shifting questions from Sales, Marketing, and FP&A into clear narratives, delivered through dashboards that get used in business reviews and forecasting
- Partner with RevOps and Marketing Ops on definitions, ownership, and the buy-in that makes them stick
Skills
- 3 to 5+ years building analytical data models in Snowflake or a comparable cloud data warehouse
- Comfortable working within an established platform and medallion layers rather than standing up your own stack
- You can build a star or snowflake schema and explain the design choices to someone who doesn't work in data
- A habit of interrogating source data instead of assuming it's clean
- Working knowledge of the CRM object model (leads, contacts, accounts, opportunities, campaigns) and how funnel metrics map onto it
- Familiar with MQL-to-SQO conversion, pipeline velocity, and what separates pipeline volume from pipeline quality
- Understand ARR, ACV, and quota structures well enough to know why a metric matters, not just how to calculate it
- Track record translating a question from a CRO or VP of Marketing into an answer they can act on
- Python for automation and scripting data quality checks
- Familiarity with marketing automation platforms and the ways data gets distorted at the point of capture
- Attribution and funnel modeling, including first-touch versus last-touch trade-offs
- Forecasting fundamentals such as pipeline coverage ratios and cohort-based forecasting
- Power BI for dashboard builds and maintenance
Benefits
- Remote work (UK time zones preferred)
- Full-time role
- Modern tooling
- No legacy debt to unwind
- Expectation that you build with AI from day one
- Real ownership over metric definitions, dimensional design, and stakeholder alignment
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