Head of Data & Analytics

Bizee•Houston, TX

12d

About The Position

Bizee (formerly Incfile) has helped over 1 million entrepreneurs start and run their businesses. We’re transforming from a transaction-focused formation business to an AI-powered operating system for entrepreneurs. We champion the everyday entrepreneur. We believe in self-determination, grit, and earned success. No fluff, no jargon, no pretense. We work hard, ship fast, and let our products speak for themselves. We’re looking for a data leader who builds. Someone who can design the data architecture that powers intelligent products, stand up the analytics that drive business decisions, and lead a team that turns raw data into competitive advantage. If you believe data is the foundation of AI, not an afterthought, this role is for you. What Makes Working Here Different Data Is the Foundation of Everything: AI-powered products are only as good as the data underneath them. You’re not building dashboards for a data warehouse; you’re designing the intelligence layer that powers an AI operating system for entrepreneurs. Greenfield Data Strategy: We’re standing up master data management, customer intelligence, marketing analytics, and 50-state jurisdictional data models. You define the strategy and build the foundation. Business-Critical Domains: Customer data, jurisdictional compliance data, marketing attribution, and financial data. These aren’t academic exercises. Getting the data model right directly impacts revenue, compliance, and company valuation. AI-Native From Day One: Every data system you build should be designed with AI consumption in mind. You’re not just making data queryable; you’re making it intelligent. The Role As Head of Data & Analytics, you own the data strategy, architecture, and intelligence capabilities for Bizee. You will design the data structures that power customer intelligence, marketing analytics, jurisdictional compliance, and financial reporting across the platform. This is not a governance or oversight role. You are a hands-on data leader who personally designs data models, reviews pipeline architecture, and writes queries to validate business logic. You lead a team of approximately 3-4 Technical Leads, Principal Data Scientists, Analysts, and Engineers providing overall leadership to 15-20 team members. You will be spending meaningful time in the work yourself. We call this a player-coach: you set the vision and strategy, then roll up your sleeves and build alongside your team. You will partner directly with Platform Engineering, Product, and Marketing leadership to ensure the data foundation enables their roadmaps. You own the data architecture decisions that determine whether the company can execute on subscription transformation, lifecycle marketing, customer intelligence, and AI-powered product experiences. This means you need deep business domain expertise. You understand how data models map to business outcomes, not just technical schemas. This is an AI-native leadership role. You design data systems with AI consumption as a first-class requirement. You use AI tools to accelerate your own work and your team’s work. You have a point of view on how modern data architecture should evolve to support AI-powered products and decision-making.

Requirements

Strategic Vision with Execution Discipline: You can articulate a 2-year data strategy and break it into quarterly milestones. You create roadmaps that stakeholders can plan against and hold yourself accountable to delivery.
AI-Native Thinking: You design data systems with AI consumption as a first-class requirement. You understand how data quality, structure, and accessibility impact AI/ML outcomes. You use AI tools to accelerate your own work.
Analytics & Intelligence: You’ve built marketing analytics, customer intelligence, or business intelligence capabilities from scratch. You know how to stand up attribution models, experimentation frameworks, and self-service analytics platforms.
Data Architecture Builder: You’ve personally designed database structures and data models that power business intelligence at scale. You understand dimensional modeling, event-driven data architectures, and how to design schemas that serve both operational and analytical workloads. You don’t just draw ERDs; you build them.
Deep Business Domain Expertise: You understand how data models map to business outcomes. You’ve worked in domains where data complexity is high (multi-entity, multi-jurisdiction, subscription lifecycle, or financial services) and you can translate business requirements into data architecture decisions.
Cross-Functional Partnership: You partner effectively with Platform Engineering, Product, and Marketing leadership. You understand their roadmaps and ensure the data foundation enables their goals. You present data strategy in business terms, not just technical terms.
Player-Coach Leadership: You lead a team of senior technical leads while staying hands-on in the work. You review data models, validate pipeline logic, and write SQL when needed. You set the vision and build alongside your team.

Nice To Haves

You can walk us through a data architecture you designed that enabled a business to make fundamentally better decisions, including the tradeoffs you navigated and what you’d do differently.
You’ve built marketing analytics or attribution infrastructure that directly influenced how a company allocated spend.
You’ve designed data models for complex, multi-jurisdictional or multi-entity businesses.
You have experience with ERP data integration (NetSuite, SAP, or similar) and understand how financial data flows through an organization.
You’ve built data platforms that serve both human analysts and AI/ML systems as first-class consumers.
Experience in the Prosumer or SMB space, e-commerce, legal tech, fintech, or compliance-heavy industries.
You can demonstrate how you’ve used AI tools to accelerate data engineering, analysis, or modeling work.

Responsibilities

Data Strategy & Roadmap: Deliver a comprehensive data strategy aligned to business priorities (subscription transformation, marketing efficiency, customer intelligence). A roadmap that Platform, Product, and Marketing leadership can plan against.
Master Data Foundation: Design and begin implementing canonical data models for Customer, Product, Jurisdiction, and Transaction domains. Establish Master Data Records with clear definitions, reconciliation rules, quality standards, and governance that the entire organization trusts.
Data Synchronization: Ensure reliable, governed data flow across CMS (Statamic), NetSuite, payment processors (Adyen), state filing systems, and customer-facing applications. Establish clear ownership, SLAs, and reconciliation processes for cross-system data integrity.
Marketing Analytics Capability: Stand up marketing mix modeling, attribution, and experimentation infrastructure. Give Marketing leadership the data visibility they need to optimize spend and prove ROI.
Customer Intelligence Platform: Build the unified customer view that enables lifecycle segmentation, churn prediction, and personalized engagement. This is the data backbone for our subscription transformation.
Self-Service Analytics: Enable Marketing, Product, and Operations teams to answer their own data questions without engineering tickets. Reduce ad-hoc data request volume by 60%+
AI-Ready Data Layer: Design data pipelines and storage patterns that serve AI/ML workloads as a first-class use case. Make it easy for product teams to build intelligent features on top of clean, well-modeled data.
Team Build-Out: Assess current team capabilities, define the target org structure, and hire or develop to fill gaps. Build a team that operates with clear domain ownership and cross-functional partnership.