About You

The SVP, Data is a senior executive responsible for leading the enterprise-wide data organization. This role defines and drives the data strategy, architecture, governance, analytics, and operations to transform data into a strategic asset. The SVP ensures data enables better decision-making, operational efficiency, innovation (e.g. AI/ML), and, where applicable, new monetization or product lines.

Your-Day-To-Day

Define a multi-year data roadmap aligned with business strategy and growth goals.
Serve as a strategic partner to executive leadership and business units, ensuring data initiatives deliver measurable business impact.
Evangelize a “data-driven culture,” building data literacy across the organization.
Lead change management in adopting new data tools, processes, and governance frameworks.

Data Architecture & Platform

Oversee the design, implementation, and evolution of scalable data platforms (cloud / on-prem / hybrid) to support analytics, reporting, AI/ML, and operational needs.
Ensure integration across data sources, real-time / batch pipelines, data warehousing, data lakes, metadata, master data, etc.
Evaluate, select, and manage external vendors, tools, and technologies that support the data ecosystem.

Data Governance, Quality & Compliance

Establish enterprise-wide data governance, standards, policies, roles, and stewardship.
Ensure data quality, consistency, lineage, security, privacy, and compliance with relevant regulations (e.g. GDPR, CCPA, industry-specific).
Monitor and enforce data controls, audit trails, access management, and data risk mitigation.

Analytics, Insights & Innovation

Oversee advanced analytics, reporting, dashboards, business intelligence, and self-service capabilities.
Drive use cases leveraging AI/ML, predictive modeling, and data science to unlock business value.
Identify opportunities for new data-driven products or services and support monetization strategies (if applicable).

Team Leadership & Operations

Build and lead a high-performing data organization, including data engineering, data science, analytics, governance teams, etc.
Set KPIs, performance metrics, and OKRs for the data function; monitor and report progress.
Manage budgets, resource allocation, recruiting, training, and career development.
Coordinate with cross-functional teams (product, engineering, operations, marketing, finance) to align priorities and execution.

Stakeholder & Communication

Present data strategy, insights, and results to C-suite, board, and key stakeholders in clear, actionable terms.
Serve as a trusted advisor to business leaders, helping them translate data opportunities into execution plans.
Foster collaboration across departments to ensure data is embedded in decision-making processes.

Your - Know - How

Required

15 years cumulatively in data, analytics, or related fields, with at least 5+ years in senior leadership roles (director / VP / SVP)
Proven success in leading complex, large-scale data transformations (architecture, governance, analytics)
Deep technical understanding of data engineering, data platforms, ETL pipelines, metadata, data lakes, etc.
Experience with cloud-based data stacks (e.g. AWS, GCP, Azure, Snowflake, Databricks, etc.)
Strong domain knowledge of data governance, privacy, security, compliance
Excellent strategic thinking, communication, stakeholder management, and influencing skills
Ability to translate business needs into data-driven solutions and deliver measurable outcomes

Preferred / Nice-to-have

Experience in your industry or vertical (e.g. fintech, healthcare, e-commerce, etc.)
History of creating revenue-generating data products or monetization strategies
Advanced degree (MSc / PhD) in Data Science, Computer Science, Statistics, Engineering, or related
Familiarity with machine learning / AI frameworks, deployments, and MLOps
Experience managing global or distributed teams

SVP, Data & AI