Manager Data Analytics & AI
Role details
Job location
Tech stack
Job description
Manages leaders and employees responsible for data, analytics, and AI enablement across development initiatives, data platforms, and application support functions. Provides portfolio-level leadership to ensure data and analytics capabilities are scalable, reusable, and aligned to business outcomes.
What You Will Do:
- Oversee enterprise-wide data, analytics, and AI enablement initiatives, including data product design, integration patterns, and AI-ready data foundations.
- Provide strategic direction to ensure data, analytics, and AI capabilities meet business needs, decision requirements, and future scalability.
- Establish and enforce standards for data quality, lineage, governance, and reuse across the portfolio.
- Lead adoption of data fabric patterns to enable federated data access with enterprise-wide guardrails.
- Partner with solution, integration, and data architects to ensure consistent implementation of data and AI patterns.
- Maximize staff and leader contribution through coaching, professional growth, and capability development.
- Monitor and maintain adherence to quality, security, and responsible AI standards on an ongoing basis.
- Ensure analytics and AI deliver actionable insights, not just reports or models., * Champions awareness of emerging trends such as AI platforms, data fabric, data products, and advanced analytics.
- Ensures senior leadership awareness of the enterprise impact of major technology trends.
- Monitors industry best practices and guides responsible adoption of new technologies.
- Provides perspective on the evolution, risks, and business impact of AI-driven capabilities.
Analytical Thinking - Level: Expert
- Designs and orchestrates the use of analytics and AI for strategic decision-making.
- Champions advanced analytics, predictive insights, and prescriptive decision support.
- Enables leaders to use analytics insights effectively, not just consume dashboards.
- Implements outcome-focused operating metrics and performance measures.
- Applies quantitative, statistical, and modeling approaches to complex business problems.
Data Fabric & AI-Ready Data Foundations - Level: Expert
- Defines and operationalizes a data fabric strategy across distributed data platforms.
- Enables federated data ownership with centralized standards for security, quality, and semantics.
- Leverages metadata, lineage, and policy-driven governance embedded directly in data flows.
- Ensures data assets are reusable, discoverable, and trusted for analytics and AI use cases.
- Aligns data fabric patterns with AI lifecycle needs, including feature reuse, explainability, and auditability.
Continuous Transformation - Level: Working Knowledge
- Leads adoption of new platforms, tools, and processes as business and technology evolve.
- Adapts operating models to support analytics-driven and AI-enabled ways of working.
- Encourages experimentation, learning, and continuous improvement.
- Communicates lessons learned from both successes and failures.
Talent Management - Level: Extensive Experience
- Builds and sustains a strong pipeline of data, analytics, and AI leadership talent.
- Coaches leaders and teams to grow strategic, not purely technical, capabilities.
- Establishes clear role expectations and development paths aligned to future needs.
- Creates an environment that attracts and retains high-impact data and analytics talent.
Leadership - Level: Expert
- Inspires teams with a clear vision for analytics-led and AI-enabled decision making.
- Coaches leaders in adaptive leadership approaches appropriate to complex, matrixed environments.
- Models behaviors that promote accountability, trust, and collaboration.
- Drives alignment around long-term data and AI strategy.
Matrix Management - Level: Working Knowledge
- Communicates effectively across business, technology, and data domains.
- Balances functional priorities with enterprise-level outcomes.
- Resolves competing requirements across solutions, platforms, and stakeholder groups.
- Maintains strong partnerships across geographic and organizational boundaries.
Vendor / Supplier Management - Level: Expert
- Manages strategic relationships with data, analytics, cloud, and AI vendors.
- Evaluates vendor roadmaps and alignment to enterprise data and AI strategy.
- Establishes best practices for leveraging external partners while protecting enterprise standards.
- Oversees integration of third-party tools into the data and analytics ecosystem.
Requirements
BS/MS in Computer Science or equivalent experience desired.
Business Acumen - Level: Working Knowledge
- Understands the organization's business model, value drivers, and financial goals.
- Communicates key considerations for business and technology decision-making.
- Translates business objectives into analytics, data, and AI priorities.
- Engages stakeholders to balance competing priorities and outcomes.
Benefits & conditions
Subject to plan eligibility, terms, and guidelines. This is a summary list of benefits.
- Medical, dental, and vision benefits*
- Paid time off plan (Vacation, Holidays, Volunteer, etc.)*
- 401(k) savings plans*
- Health Savings Account (HSA)*
- Flexible Spending Accounts (FSAs)*
- Health Lifestyle Programs*
- Employee Assistance Program*
- Voluntary Benefits and Employee Discounts*
- Career Development*
- Incentive bonus*
- Disability benefits
- Life Insurance
- Parental leave
- Adoption benefits
- Tuition Reimbursement