About the Role
The Senior Vice President Information Technology, Enterprise Data and AI is responsible for building and scaling a product-grade, enterprise data and AI platform that accelerates business outcomes. This leader sets the vision and drives execution across data engineering, analytics, and AI, partnering closely with Product, Engineering, and Business leaders to embed data and intelligence directly into products, workflows, and decision-making. This role balances strategic leadership with hands-on technical depth, operating with a strong bias toward delivery, platform reliability, and customer.
Responsibilities
- Product-Led Data & AI Strategy: Define and own the enterprise data and AI product vision, roadmap, and operating model aligned to company strategy. Treat data platforms, analytics, and AI capabilities as products with clear customers, SLAs, adoption metrics, and ROI. Partner with Product and Engineering leaders to embed analytics, ML, and GenAI into core products and internal platforms.
- Data Platforms & Engineering Excellence: Lead the design, build, and operation of scalable, cloud-native data platforms, including ingestion, transformation, lakehouse/warehouse, streaming, and BI layers. Establish engineering standards for data quality, reliability, security, performance, and cost efficiency. Drive modernization from legacy systems to modern data architectures, balancing speed, resilience, and technical debt reduction.
- Analytics, AI & ML Enablement: Enable teams to deliver production-ready analytics, ML, and AI solutions that solve real customer and business problems. Establish pragmatic MLOps / AI operational practices to move from experimentation to repeatable value. Champion responsible, governed use of AI while accelerating adoption across products and teams.
- Operating Model, Governance & Delivery: Define DataOps / Software Development Life Cycle (SDLC) practices that align with product and engineering delivery models. Implement enterprise data and AI governance (quality, privacy, security, responsible AI) without slowing innovation. Own platform KPIs, including data quality, time-to-value, platform adoption, and cost management.
- Leadership & Collaboration: Build and lead high-performing teams across data engineering, analytics, and data science. Act as a hands-on leader when needed, unblocking teams, reviewing designs, and accelerating delivery. Drive alignment across Product, Engineering, Security, Legal, and Business stakeholders in a matrixed environment.
Required Qualifications
- 15 to 20 years of experience across data engineering, analytics, and AI, with senior leadership experience in product- or engineering-led organizations.
- Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or related field.
- Proven track record building and scaling enterprise data platforms as products in complex environments.
- Deep understanding of modern data architectures, cloud platforms, and analytics/ML systems.
- Demonstrated ability to translate business and product needs into shippable, reliable data and AI capabilities.
Preferred Qualifications
- Masters degree in Computer Science, Software Engineering, Computer Engineering, or related field.
- Experience in Property Management or Multi-Family housing industry.
- Strong executive presence with the ability to influence, prioritize, and drive outcomes across teams.