VP of Data

ButterflyMX • ,

9d • $250,000 - $300,000 • Remote

About The Position

ButterflyMX is seeking a world-class Vice President of Data to spearhead a company-wide data transformation. This role aims to establish data as a critical operating advantage by leveraging existing foundational technologies like Snowflake, Fivetran, dbt, Sigma, and modern AI platforms. The VP of Data will be responsible for establishing Snowflake and a governed data layer as the company's single source of truth, ensuring trusted golden records for business entities and standardized definitions for key metrics. The goal is to empower all functions to understand performance, diagnose issues, identify opportunities, and make faster, more confident decisions. Success will be measured by the quality and speed of decisions, adoption and trust in data products, and the overall multiplication of team effectiveness through data. This is a high-visibility leadership position reporting to the CTO, with initial direct reports and broad influence across various departments.

Requirements

• 12+ years of progressive experience across data engineering, analytics engineering, business intelligence, data architecture, data products, or related disciplines.
• 5+ years leading professional data teams, including experience managing managers or senior technical leaders.
• Demonstrated success building or transforming a data function within a growing SaaS or technology company of comparable scale.
• Deep experience with modern cloud data platforms, preferably including Snowflake.
• Strong experience with data transformation and modeling frameworks such as dbt.
• Experience with managed ingestion platforms such as Fivetran and with designing reliable source-to-warehouse pipelines.
• Strong experience with business intelligence and self-service analytics platforms such as Sigma.
• Deep understanding of dimensional modeling, semantic layers, entity resolution, master data, golden records, data contracts, lineage, observability, and quality engineering.
• Experience integrating and governing data from Salesforce and other core SaaS business systems.
• Demonstrated ability to establish governed business metrics and resolve cross-functional definition disputes.
• Strong commercial understanding of recurring-revenue business models and SaaS operating metrics.
• Experience designing data products for executive, operational, analytical, and machine consumers.
• Experience supporting planning, forecasting, customer lifecycle analysis, go-to-market analytics, financial reporting, and product analytics.
• Personally built and shipped at least one production AI agent or agentic workflow.
• Strong understanding of AI-agent evaluation, tool access, context management, observability, permissions, security, and operational reliability.
• Hands-on technical capability to write and review SQL, inspect dbt projects, evaluate models, troubleshoot pipelines, and prototype solutions.
• Exceptional written and verbal communication.
• Demonstrated ability to influence senior executives and drive difficult cross-functional changes.
• Bachelor’s or advanced degree in a relevant technical, quantitative, or business field is welcome but not required. Exceptional experience, judgment, and results matter more than credentials.

Nice To Haves

• Visionary and Transformational: Clear point of view on world-class data organization, ability to translate vision into executable sequence, led meaningful transformation, create momentum while building enduring foundations, distinguish transformative priorities from attractive distractions.
• Commercially Fluent: Speak the language of business (ARR, bookings, retention, etc.), understand how SaaS businesses create and lose value, connect data investments to revenue, cost, customer outcomes, risk, and organizational effectiveness, challenge business assumptions credibly, interested in decisions and economics.
• Technically Credible: Deep knowledge of modern data architecture, engineering, analytics engineering, governance, quality, and BI; challenge architecture decisions, capable of writing code, reviewing models, debugging pipelines, prototyping solutions, senior enough to set strategy but not detached from implementation, understand technical simplicity vs. rigor.
• Operationally Grounded: Built or transformed data function at comparable scale/complexity/growth, experience not limited to early-stage startup or large enterprise, know how to sequence investments when immediate answers are needed but foundations are incomplete, operated through ambiguity/imperfect systems/limited capacity/competing priorities, build disciplined but not cumbersome processes.
• Agent-Fluent: Use AI agents as normal work tool, personally built and shipped at least one production agent creating value, understand agent architecture, tool use, context, evaluation, observability, permissions, failure modes, human oversight, identify workflows genuinely improved by agents, turn prototypes into dependable capabilities.
• Product-Minded: Treat datasets, metrics, semantic models, dashboards, and agent interfaces as products; care about users, adoption, discoverability, usability, trust, support, versioning, deprecation; understand shipping a dashboard is not changing a decision; simplify data usage experience; measure intended business outcomes.
• Politically Mature: Navigate disagreement without becoming a weapon, understand metric disputes reflect real differences in incentives/workflows/definitions/decision needs, listen carefully, identify underlying issues, facilitate principled resolution, build relationships without sacrificing independence, tell executives when their interpretation is unsupported while preserving trust, know when to compromise on implementation vs. truth.
• Truth-Seeking and Principled: Willing to disagree when evidence disagrees, distinguish confidence from certainty, make assumptions explicit, do not manipulate definitions/analyses for desired answers, communicate inconvenient findings diplomatically but directly, relentless about truth while open to being wrong, demonstrate sound judgment, integrity, and intellectual honesty.
• Headstrong and Collaborative: Build broad support for difficult changes, empathetic toward stakeholder constraints without allowing them to become permanent excuses, push hard without being needlessly adversarial, absorb disagreement, remain composed, drive toward right outcome, create clarity, establish ownership, follow through until change is implemented.

Responsibilities

• Define and execute ButterflyMX’s enterprise data strategy.
• Prioritize transformation work based on commercial impact, decision value, risk, and organizational leverage.
• Balance foundational investments with rapid delivery of visible business value.
• Establish the governed data layer, primarily centered on Snowflake, as ButterflyMX’s authoritative source of truth.
• Ensure leaders can clearly understand performance, diagnose problems, identify root causes, and act confidently.
• Translate business questions into durable analytical systems rather than one-time analyses.
• Partner with Finance, Sales, Marketing, Customer Success, Product, and Operations to define the economic and operational relationships that drive company performance.
• Identify leading indicators and causal relationships, not merely lagging reports.
• Create mechanisms that reveal emerging risks and opportunities before they become obvious in monthly or quarterly reporting.
• Improve planning, forecasting, resource allocation, prioritization, and accountability throughout the organization.
• Establish a company-wide metric governance framework.
• Treat data products with the same rigor applied to strong external software products.
• Define users, use cases, adoption goals, trust requirements, service levels, documentation, and success measures for each important data product.
• Design data experiences that are intuitive, discoverable, and easier to use than informal alternatives.
• Measure adoption, usability, reliability, consumer satisfaction, and decisions influenced.
• Build a data organization in which AI agents are a primary working tool, not an experiment or side project.
• Remain technically engaged enough to review code, inspect models, prototype solutions, and participate directly when difficult problems require senior judgment.
• Engineer data quality into the platform rather than relying on manual review and reconciliation.
• Centralize standards, architecture, governance, and core data products while decentralizing responsible usage.
• Develop strong partnerships with every major business function.
• Lead, develop, and expand a high-performing data organization, beginning with four direct reports.

Benefits

• Comprehensive Medical, Dental and Vision plans (ButterflyMX covers 80% of the cost) starting day 1
• 401(k) plan with a match
• 10 paid holidays, 20 vacation days, 5 sick days, 3 floating holidays
• Basic Life and Accidental Death and Dismemberment Insurance (ButterflyMX covers 100% of the cost)
• Short and Long Term Disability (ButterflyMX covers 100% of the cost)
• Paid Family Leave
• Employee Assistance Program
• Quarterly self-care stipends
• Access to optional benefits including pre-tax flexible healthcare spending accounts (FSA and HSA), Dependent Care FSA, and Commuter Benefits, as well as optional Supplemental Life, AD&D, Hospital Indemnity, Legal, Accident, Critical Illness, Pet, and Personal Liability Insurance

What This Job Offers

• Job Type: Full-time
• Career Level: Executive
• Education Level: No Education Listed