GTM Analytics Lead

Our Mission

ButterflyMX is on a mission to empower people to open and manage doors & gates from a smartphone. Our products are installed in more than 20,000+ multifamily, commercial, gated communities, and student-housing properties worldwide, including properties developed, owned, and managed by the most trusted names in real estate. Our features are designed for developers, owners, property managers, and tenants and our products lower operating costs and improve tenant satisfaction.

Our Solution

Developers and owners no longer need to run building wiring or install in-unit hardware. Property managers can grant building access, revoke permissions, and review entry logs from an online dashboard. Residents can open doors from their smartphones, issue visitor access, and see who is trying to enter the building.

Our Culture & Values

Fantastic people are the key to our success. As a distributed, primarily remote workforce, we’re looking for more intelligent, passionate, collaborative, ai-forward, and down-to-earth individuals to join our growing team. We’re driven by a shared commitment to excellence and innovation, grounded in our core values: We delight our customers, We take ownership, We are a community of collaborators, We speak up, We think big and do small, and We are tenacious.

Role Overview

ButterflyMX is seeking a GTM Analytics Lead to own the data and decisioning foundation of the Sales organization and evolve it into the trusted intelligence layer that powers every Sales decision, planning cycle, and GTM automation we run.

This role sits at the center of how we understand our business. You will own the canonical revenue data model, govern all metric definitions, and ensure every dashboard, report, and data feed the Sales org depends on is accurate, consistent, and decision-ready. The VP, Director, and Business Partners carry the narrative to Leadership; you own the data layer that makes that narrative trustworthy and unimpeachable.

This is a senior individual contributor role at the intersection of data engineering, GTM analytics, and revenue operations. You will operate with significant autonomy within the Sales data and intelligence domain, provide impact directly to Sales Leadership and key partners across Finance, Marketing, and Product, and be expected to proactively identify what needs to be built, not just execute against what’s handed to you.

When this role is working well, leadership moves faster because the data is never in question, analysis is never challenged on credibility, and the Sales Ops team spends its time with cross-functional stakeholders on judgment rather than reconciliation.

How You Work

You are obsessive about data accuracy. When a number is wrong in a dashboard or an exec deliverable, you feel it personally. You don’t wait to be told. You catch it, fix it, and close the gap in the data model so it doesn’t happen again.

You build infrastructure, not one-offs. You default to codifying things: SQL, dbt models, governed metric definitions. Every manual spreadsheet you touch becomes a process you automate. You leave the data layer cleaner than you found it.

You get the business, not just the data. You understand how pipeline moves, how deals close, and how territory and quota decisions get made. You use that context to build data models and dashboards that are actually useful, not just technically correct.

You surface problems within your domain before being asked. Within the Sales data and intelligence layer, you proactively spot quality gaps, metric inconsistencies, and missing visibility, while bringing a point of view on what to address next rather than waiting for a request.

You manage your own workload without constant direction. Demand on this role will outpace capacity. Sales, Finance, Marketing, and Product all have asks. You sequence your own work day-to-day, stay focused on what matters most, and raise conflicts clearly rather than silently absorbing everything.

You execute with ownership. Given clear direction and context, you scope, build, and deliver without needing to be managed through it. You come back with what you learned, what’s next, and where you need a decision.

Responsibilities

Own the canonical revenue data model and all metric definitions, ensuring consistency of data definitions, tables, and lineage across all Sales systems and vendor data sources, while governing calculation standards for ARR, pipeline, win rate, conversion, velocity, and all other revenue metrics used in Sales reporting and planning; when this is done well, metric definitions are never debated in executive discussions and analysis is never challenged on the credibility of its underlying data

Build and maintain a unified revenue data and business logic layer combining Salesforce, Snowflake, and third-party vendor sources; audit continuously for quality gaps, metric drift, and inconsistencies; this is the foundation everything else in the intelligence stack is built on

Own all BI dashboards for the Sales organization, from executive KPIs to rep-level performance views

Produce the decisioning outputs that drive the revenue operating rhythm, from regular-cadence data packages for QBRs, forecasting, and pipeline reviews, to structured outputs that support annual planning, quota-setting, territory design, and capacity modeling; the goal is that leadership always has what it needs to move with confidence, not wait for data to be ready or reconciled

Provide clean, reliable, and well-documented data inputs to power GTM automation; partner with the GTM Engineer to validate inputs and flag data quality issues

Establish and automate repeatable data processes in SQL, replacing manual spreadsheet workflows across Sales Operations and Sales Leadership, converting recurring manual work into reliable infrastructure and reducing time-to-insight for the team

Coordinate with Analytics Engineering and Business Systems on Sales data modeling and data quality, from dbt transformations of Salesforce data into exec reporting

Requirements

Strong SQL skills; production-quality queries, well-documented data models, and code written as though others will maintain and build on it

Experience in data architecture, management, and warehousing; Snowflake strongly preferred

Hands-on experience with Salesforce data, including schema familiarity, field-level data quality patterns, and how Salesforce data flows into downstream reporting and analytics systems

Proficiency in modern BI tools such as Sigma Computing, Hex, Omni, Tableau, or equivalent with a track record of dashboards that are trusted and actively used

Demonstrated experience building and maintaining a unified data and intelligence layer that is clean, governed, and serves as a genuine single source of truth

Experience supporting strategic planning cycles — including quota-setting, capacity modeling, or territory design — with structured, data-backed outputs

Ability to engage directly with Sales Leadership, Finance, and Marketing as a credible data expert, translating technical complexity into clarity without sacrificing rigor

Background in Data Analytics, Analytics Engineering, GTM Analytics, or Business Intelligence with strong GTM and Sales fluency; Revenue / Sales Operations backgrounds with equivalent technical depth are also well-suited for this role

Preferred

Familiarity with multi-channel GTM data environments (e.g., Direct Sales, Channel/Reseller) and the data modeling complexity that comes with tracking pipeline and revenue across GTM motions and customer segments

Experience with businesses that sell hardware and software together, where GTM motion, pipeline data, and customer lifecycle span both

Experience with multi-product data architectures where products are sold individually or as packaged offerings, where pipeline and revenue need to be tracked at the product/SKU level

Exposure to real estate, P