Head of Data & AI Enablement

PushPress

3d

About The Position

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.

Requirements

• 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 Haves

• 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

Responsibilities

• Data Strategy & Infrastructure
• 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
• Balancing Product & Internal Data Needs
• 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
• AI Collaboration
• 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
• External Products & Reporting
• 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
• Analytics & Insights
• 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
• Team & Culture
• 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 This Job Offers

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