Senior Manager, Business Intelligence & AI Analytics

The Sr. Manager, Business Intelligence is a senior individual contributor on the Sales BI team within the Sales Business Office organization, driving the development and delivery of analytics and insights that power the Cox Automotive sales organization. This role pairs deep, hands-on technical BI expertise with a forward-looking mindset on AI-driven analytics, operating as a trusted advisor to sales leadership and a technical leader across the Sales Business Office who drives impact through expertise and influence rather than direct people management.

A key focus for this hire is to lead the team's AI transformation, drawing on direct experience having led one before: setting direction, shipping AI agents and generative BI into production, and proving measurable adoption and business impact for sales stakeholders. This person will be a champion for moving the team beyond traditional BI toward an AI-augmented analytics function.

Primary Duties & Key Responsibilities

Analytics Strategy & Impact

• →Acquire, synthesize, and organize business data from internal and external sources to produce insights that drive sales performance and revenue growth

• →Serve as a trusted advisor to multiple sales and business partners across a wide range of analytical work, from recurring reporting and ad-hoc requests to large-scale cross-functional engagements

• →Co-own the Sales BI roadmap with other BI, Metrics & Reporting, and allied teams, setting clear direction and priorities for data collection, reporting, and AI-enabled insight delivery

• →Define the metrics and measurement framework sales leadership uses to run the business, including how AI-generated insights are validated and trusted

• →Shape the direction of Cox Automotive's BI and AI analytics infrastructure with Metrics & Reporting, IT, Engineering, and data platform teams, including data warehousing (Snowflake), reporting (Power BI), and AI analytics platforms (Amazon Quick)

• →Lead complex initiatives spanning multiple product lines and areas of the business, from scoping through measurable outcomes

AI Transformation & Innovation

• →Set and execute the AI strategy for Sales BI: decide which tools, models, and agentic frameworks the team adopts (e.g., Claude, Snowflake Cortex, Amazon Quick Suite), and retire legacy methods as AI replaces them

• →Architect and deliver production AI agents and automated analytical workflows that sales stakeholders use daily, and set the reusable patterns other analysts build on

• →Build and prioritize a portfolio of AI use cases across the Sales Business Office, each with a clear business case and measured results such as adoption, hours saved, and revenue influence

• →Serve as the Sales Business Office's AI subject matter expert, staying current on emerging tools and coaching analysts and business partners on practical AI applications

Technical Leadership & Mentorship

• →Act as a hands-on technical leader for the BI team, setting the bar for analytical quality, reusable data models, and engineering best practices

• →Lead the team's AI upskilling and change management: build the learning path, model new ways of working, and help analysts move from building reports to delivering AI-augmented insights, without direct people-management responsibility

Stakeholder Partnership

• →Translate complex, multi-source data into clear, relevant recommendations for non-analytical sales leaders and stakeholders

• →Communicate findings throughout the organization, from analysts to executive leadership, inspiring decision-makers to adopt bold strategies and helping business and tactical teams execute thems

• First 90 days: assess the current Sales BI stack and AI readiness, and present a prioritized AI roadmap to BI and sales leadership

• Within 6 months: at least two production AI agents or automated workflows in daily use by sales stakeholders, with adoption and time-saved metrics reported

• Within 12 months: a measurable shift in how Sales BI delivers analytics, with fewer manual reports, more self-serve and AI-generated insight, a governance-approved path for scaling new AI use cases, and analysts building on the patterns this role established

Minimum Requirements:

• Applicants must currently be authorized to work in the United States for any employer without current or future sponsorship. No OPT, CPT, STEM/OPT or visa sponsorship now or in future.
• Preference toward Atlanta based candidates
• Bachelor's degree in a related discipline and 8 years' experience; or a Master's degree and 6 years' experience; or 16 years' experience in a related field
• 2+ years of experience applying AI in an analytics or data context, including hands-on use of LLMs (e.g., Claude, ChatGPT, Copilot) and Snowflake AI/Cortex, and experience leading at least one analytics AI transformation end to end: AI agents or automated analytical workflows in production, used by business stakeholders, with measured adoption and impact

• 6+ years of hands-on experience with analytics, automated reporting, data exploration, and data visualization

• 6+ years of BI development experience required, including building enterprise-grade Power BI dashboards, data models, DAX measures, and row-level security; experience as a primary owner of a reporting platform serving hundreds of users strongly preferred

• 8+ years of SQL development experience required, with proficiency writing complex queries, CTEs, and transformations against large datasets; Snowflake experience strongly preferred
• Experience serving as the technical lead on cross-functional analytics initiatives spanning multiple teams or business units (direct people-management experience is not required for this individual contributor role)

• Advanced proficiency in analytical thinking, business acumen, consulting, data gathering and reporting, and project administration & management

• Advanced proficiency in building partnerships, collaborating with intent, communicating with consideration, developing trust, and driving innovation

• Track record of influencing executive decisions with data and AI-driven insight, including presenting to large audiences and senior business leaders

• Strongly preferred: a proven track record leading change management for an analytics team's adoption of AI, including upskilling analysts and retiring legacy reporting

• Strongly preferred: experience partnering with IT, Security, and governance teams to get AI use cases approved and scaled within enterprise data and privacy policy

• Hands-on experience with Amazon Quick Suite (generative BI, research agents, Quick Flows and Quick Automate, and Spaces) or similar enterprise agentic analytics platforms