Head of Data & AI Enablement

About PushPress PushPress is the AI-powered gym management platform built for boutique fitness. We are transforming how boutique fitness owners operate and how the entire $100B global fitness industry connects, transacts, and grows. Trusted by more than 5,000 gyms and 500,000 members, PushPress processes ~$1B annually. We're a Series B company backed by Altos Ventures, StepStone, and Mucker Capital, and we're going all-in on AI. Our AI Assistant, AI Member Intel, and AI-powered reporting tools are already changing how gym owners and coaches operate. We believe AI should make the human side of fitness better, not replace it. By embedding intelligence directly into the product, we enable boutique fitness owners to make faster decisions, unlock new revenue streams, and collaborate across a connected network. As more gyms join the platform, data compounds, intelligence strengthens, and the value of the ecosystem increases for every owner. We are a global team of builders, operators, and fitness fanatics on a mission to level the playing field for independent fitness entrepreneurs. If you are ready to help reshape an industry, The Role We're looking for a senior leader to own our data function and AI infrastructure. As our first Head of Data & AI Enablement, you'll define and execute the company's data strategy from the ground up — and critically, you'll need to build organizational buy-in for that strategy and drive it to measurable outcomes. You'll own data engineering, pipeline architecture, analytics, and the data layer that feeds our AI and reporting products. Our engineering team currently owns AI infrastructure and feature development — this role ensures they have the clean, reliable, well-structured data foundation to do that effectively. This is a player-coach role at a growth-stage company. You'll set the vision and roadmap, but you'll also roll up your sleeves early on. A key challenge of this role is balancing the day-to-day demands — data quality issues, stakeholder requests, system syncs — with execution on a longer-term data roadmap. We need someone who won't let firefighting crowd out the strategic work. This role sits at the intersection of data, business strategy, and AI. You'll work closely with Dan and the leadership team to ensure our data platform powers both internal decision-making and the products our engineering team is building for customers. You'll serve as a critical bridge between the business side and the data engineering function — translating business needs into data requirements, and ensuring data work is always grounded in business context and value. On AI specifically, you'll be a key voice in shaping our approach — bringing experience with LLMs and AI agents to the table — but you won't be doing it alone. How we adopt and operationalize AI tooling is something the company is actively figuring out, and this role will help shape that alongside engineering and product leadership. What You'll Own

Develop a clear, actionable data strategy — and own the process of getting buy-in across leadership, engineering, and product to execute it successfully

Architect and scale our data platform end-to-end — ingestion, transformation, storage, and serving — with a modern, layered approach (e.g., raw → cleaned → standardized metrics) that enables self-serve access across the company

Ensure data is synchronized, consistent, and reliable across all internal systems and tools (billing, CRM, product analytics, support, etc.)

Build and maintain the pipelines that feed our AI features, reporting products, and internal analytics

Establish data governance, quality standards, and observability practices as we scale

Make smart architecture and infrastructure decisions — knowing when to build, buy, or integrate — with a practical, data-informed perspective

Navigate the tension between building data capabilities for customer-facing products and investing in internal analytics and infrastructure — both are critical, and this role must keep them in balance

Understand the product development cycle well enough to anticipate data needs before they become blockers

Proactively plan data collection and instrumentation for upcoming product features, rather than reacting to requests after the fact

Ensure the right data is available, clean, and structured so engineering teams can build and ship AI features (AI Member Intel, AI Assistant, AI Reporting) confidently

Bring hands-on experience with LLMs and AI agents to help shape the company's evolving AI strategy — alongside engineering and product leadership

Contribute to build-vs-buy-vs-integrate decisions with a practical, data-informed perspective

Stay close to the evolving AI landscape so you can be a credible thought partner to the teams building on top of your data platform

Own the data layer behind reporting features that gym owners use to understand their business — revenue trends, member engagement, class performance, churn signals, and more

Partner with product and design to ensure the underlying data is accurate, performant, and structured to support simple, actionable insights for non-technical users

Provide the data foundation that enables product and engineering to build differentiated, AI-powered experiences

Build the analytics foundation that enables the company to make faster, better decisions

Partner with go-to-market, product, and finance teams to deliver the data and reporting they need

Develop internal dashboards, self-serve tools, and reporting capabilities that scale with the company

Build and lead a high-performing data and AI team as the company grows

Set the technical direction, hiring plan, and team culture for the function

Foster a data-informed culture across the organization — make data accessible, understandable, and trusted

What We're Looking For

8+ years of experience across data engineering, analytics, and AI, with at least 2 years in a senior leadership role

Deep hands-on experience building and scaling data platforms in a cloud environment (we're on AWS

)Strong IC foundation across multiple data disciplines — you've done the work yourself before leading others through it

A systems thinker who understands business context deeply, not just technical architecture 

Strong understanding of modern data stack tooling — warehousing, ETL/ELT, orchestration, and BI

Familiarity with the AI/ML landscape — you don't need to train models from scratch, but you should know how to evaluate tools, APIs, and approaches and make smart infrastructure decisions that support AI-powered products

Track record of building and managing high-performing technical teams

Proven ability to develop a data strategy, build cross-functional buy-in, and execute it to measurable results — whether hands-on or by empowering your team

Ability to think strategically about where AI creates real value and where it doesn't

Comfortable operating in a fast-moving, resource-constrained environment where you'll need to prioritize ruthlessly

Excellent communicator who can translate technical concepts for non-technical stakeholders and serve as a bridge between business teams and data engineering

Hands-on experience with LLMs and AI agents in production systems

Background in data synchronization across multiple product surfaces and third-party integrations

Nice to Have

Experience at a B2B SaaS company, ideally serving SMBs

Familiarity with vertical SaaS or fitness/wellness industry dynamics

Data science background — not necessarily ML-focused, but understands data transformation and modeling deeply