Director of Data, Analytics & AI

Job Description

Sage is searching for a Director to lead the consolidation, modernization and AI-native transformation of its North American Data, Analytics & AI capability. This role exists to bring together today’s disparate analytics, BI and data engineering teams into a single, cohesive, product-led function that operates as the trusted source of insight for the GTM organization.

This is an opportunity to lead a major data transformation program — consolidating fragmented data assets, tools and platforms into a unified, governed enterprise data ecosystem — while simultaneously upskilling the team for the AI-native era and embedding modern data management practices at scale.

This is a builder’s role. You will own the forward-looking data acquisition strategy, define and execute the analytics and AI product roadmap, and apply UX and persona-driven thinking to ensure data products are adopted and trusted by GTM stakeholders. You will lead through influence in a global, matrixed organization, partnering with functions that do not directly report to them, and will personally coach the team to deliver deep analytical insight projects that drive measurable commercial outcomes.

To be successful, you must bring extensive enterprise data leadership experience, product lifecycle fluency (including SDLC), a track record of large-scale technology and database conversions, and the credibility to be a trusted adviser to GTM executives in a high-growth SaaS environment.

Key Responsibilities

Strategic Leadership:

Develop and execute a comprehensive business intelligence and AI strategy aligned with SaaS business models and organizational goals.
Own the North America go-to-market AI/BI strategy and roadmap, aligned to SaaS GTM objectives; set objectives and key results linked to revenue, retention, efficiency, and customer experience.
Build and run a BI/AI Center of Excellence, standards, and reusable assets for GTM analytics.
Champion the adoption of AI-powered tools and platforms to drive innovation and measurable business outcomes.
Responsible for change management ownership for AI and executive stakeholder alignment.

AI Enablement & Innovation:

Stand up agentic workflows (e.g., lead routing, forecast hygiene, account insights, next‑best‑action) and maintain lifecycle management (versioning, monitoring, rollback).
Identify and prioritize AI use cases in sales enablement, marketing automation, and revenue operations (e.g., opportunity routing, churn detection, advanced analytics).
Oversee the deployment, governance, and lifecycle management of AI agents and solutions.

Data Management:

Establish and evolve BI and AI architecture to support reporting needs across multiple data sources and platforms.
Oversee cloud data architecture (e.g., Snowflake/Databricks + ETL/ELT), semantic models, and self‑service analytics; ensure scalability and cost discipline.
Ensure data quality, lineage, and cataloging; partner with IT/Data Eng to maintain secure integrations with CRM (Salesforce), MAP, CS tools.
Implement and govern a responsible AI framework including fairness, privacy, transparency, human oversight, risk reporting, and periodic audits. Own ethical AI practices such as bias mitigation, model transparency, and remediation planning.

Team Management:

Lead and mentor a team of data analysts, BI professionals, and AI champions.
Foster a culture of innovation and AI literacy, including training, certifications, and participation in AI hackathons.

Reporting, Analysis & Collaboration:

Direct the creation of dashboards, reports, and visualizations that incorporate AI-driven insights.
Analyze complex data sets using advanced analytics and machine learning to identify trends, patterns, and opportunities for improvement.
Facilitate cross-departmental collaboration to ensure data- and AI-driven decision-making

Qualifications:

Minimum of 5 years in leadership and 10 years of working experience in business intelligence, AI, data analytics, or a related field.
Proven experience with BI tools (e.g., Tableau, Power BI, MicroStrategy), data management systems (Oracle DB, Snowflake), and AI platforms (Microsoft Copilot, Nexus).
Experience in SaaS environments and working with Salesforce is an asset.
Executive Influence & Stakeholder Management: Ability to engage senior leadership, drive consensus, and influence strategic decisions using data and AI insights.
Change Leadership: Proven capability to lead organizational transformation, including AI adoption and analytics-driven culture.
Business Acumen: Deep understanding of SaaS economics, GTM motions, and how AI/BI initiatives impact revenue, retention, and operational efficiency.
Advanced Data Architecture Knowledge: Expertise in modern cloud data platforms (Snowflake, Databricks), semantic modeling, and scalable BI frameworks.
Applied AI & Machine Learning: Hands-on experience with AI agent development, orchestration, and lifecycle management; familiarity with LLM-based solutions and predictive modeling.
Data Governance & Responsible AI: Strong grounding in compliance (GDPR, CCPA, PIPEDA), ethical AI principles, and risk mitigation strategies.
Program Management: Ability to manage complex, multi-workstream programs with clear OKRs tied to business outcomes.
Budget & Vendor Management: Skilled in negotiating contracts, managing budgets, and tracking ROI for analytics and AI investments.
Metrics & Impact Orientation: Expertise in defining and tracking KPIs/OKRs that link analytics initiatives to measurable business impact.
Executive Storytelling: Ability to craft compelling narratives from complex data for C-suite audiences.

The compensation offered will be determined by factors such as location, level, job-related knowledge, education, and experience. Certain locations require job postings to include a reasonable estimate of the salary range applicable to the role.

For this role, in those locations, the target salary range for new hires is $180K salary to