Vice President of Data

We are seeking a visionary and strategic Vice President of Data to lead our data organization. This role is responsible for understanding our products and business strategy to a deep level, and from there shape and execute the company’s data strategy. The role must ensure data-driven decision-making, and foster a culture of analytics excellence. The VP of Data will oversee data engineering, analytics, governance, and data science initiatives to drive business growth and operational efficiency.

Key Responsibilities:

• Data Strategy & Leadership: Define and implement a company-wide data strategy aligned with business objectives. Act as a key advisor on all data-related matters to the executive leadership team.
• Data Engineering & Architecture: Oversee the development and maintenance of a scalable and robust data infrastructure that enables seamless data collection, processing, and analysis.
• Analytics & Business Intelligence: Drive the adoption of data-driven decision-making across departments by implementing and enhancing analytics tools, dashboards, and reporting capabilities.
• Data Science & AI: Lead advanced analytics, machine learning, and AI initiatives to unlock new business opportunities and improve operational efficiencies.
• Data Governance & Compliance: Ensure data integrity, security, and regulatory compliance, establishing best practices in data privacy and ethical data use.
• Cross-functional Collaboration: Partner with Product, Engineering, Marketing, Finance, and other teams to integrate data solutions that enhance performance and innovation.
• Team Leadership & Development: Build, mentor, and scale a high-performing data team, fostering a culture of continuous learning and innovation.

Core Competencies and Skills:

• 10+ years of experience in data leadership roles, with a proven track record of driving data strategy in high-growth environments.
• Strong leadership and team-building skills, with the ability to inspire and develop top-tier data professionals.
• Strong expertise in data engineering, analytics, data science, and governance.
• Hands-on experience with cloud-based data architectures (AWS preferred) and modern data stack technologies (e.g., Snowflake, BigQuery, Databricks, DBT, etc.).
• Deep understanding of machine learning, AI, and predictive analytics applications in business is a plus.
• Experience working in regulated environments (e.g., finance, healthcare) is a plus.
• Excellent communication skills, with the ability to translate complex data insights into actionable business strategies.