Analytics Enablement and Governance Lead

The Manager, Analytics Enablement & Governance will serve as the horizontal enablement and governance leader for the centralized Mopar Parts & Services Business Analytics organization. Reporting directly to the Director of Business Analytics, the role will establish the standards, processes, and decision routines that enable domain teams to work with clear priorities, trusted data, consistent delivery practices, and shared portfolio visibility.

The role is accountable for analytics governance, intake and prioritization, KPI and metric standards, report rationalization, data quality, BI certification, analytical-product lifecycle management, and cross-team consistency. It partners with domain Analytics Managers, Business Analysts, Reporting Analysts, Data Scientists, ICT, data owners, engineering teams, and business stakeholders.

The Manager supports BI, the analytics data foundation, advanced analytics, forecasting, and AI governance without owning every dashboard, dataset, or model. The focus is equipping domain teams with practical frameworks, reusable tools, and quality controls that improve trust, reduce duplication, accelerate delivery, and preserve flexibility for distinct business needs.

Key Responsibilities:

· Operating model and governance: Establish the analytics governance framework, decision rights, forums, role clarity, escalation paths, and controls used across the organization.

· Demand and portfolio management: Lead consistent intake, prioritization, capacity planning, backlog management, and portfolio reporting across analytics demand.

· KPI and semantic governance: Govern KPI definitions, business rules, ownership, calculation logic, semantic standards, and reuse of approved metrics and datasets.

· Reporting governance: Define dashboard standards, certification, inventories, usage monitoring, and rationalization of redundant or low-value reporting.

· Data quality and readiness: Establish standards for quality, lineage, metadata, access, documentation, testing, issue management, and production release readiness.

· Advanced analytics and AI governance: Partner with Data Scientists and domain leaders on practical standards for forecasting, experimentation, model validation, monitoring, responsible AI, deployment, and retirement.

· Technology coordination: Clarify handoffs, data-product requirements, platform dependencies, release responsibilities, and production support expectations with ICT and engineering partners.

· Adoption and consistency: Lead training, communications, and communities of practice while balancing enterprise standards with unique domain needs.

· Continuous improvement: Monitor governance and delivery health and sponsor improvements in speed, quality, reuse, transparency, and business value.

Basic Qualifications:

· Bachelor’s degree in Business Analytics, Data Analytics, Information Systems, Computer Science, Engineering, Finance, Supply Chain, Business Administration, or a related field.

· Minimum 10 years of progressive experience in analytics governance, business intelligence, data management, analytics operations, product management, or a related discipline, including cross-functional leadership.

· Experience establishing governance standards, intake and prioritization models, reporting practices, data-quality controls, or analytical delivery processes.

· Strong knowledge of BI and reporting, analytics data foundations, KPI definitions, semantic concepts, analytical-product delivery, validation, documentation, and lifecycle management.

· Demonstrated ability to translate strategy into practical routines, standards, decision rights, and measurable improvements.

· Strong leadership, communication, facilitation, prioritization, stakeholder management, and change-management skills.

Preferred Qualifications

· Experience in automotive aftersales, parts, dealer operations, supply chain, warranty, service contracts, marketing, eCommerce, finance, sales operations, or related functions.

· Experience working across multiple business functions or helping establish or scale a centralized analytics, BI, or data governance capability.

· Familiarity with Power BI, Streamlit, Excel, SQL, Snowflake, Databricks, Azure, Jira, Azure DevOps, Git, or comparable tools.

· Familiarity with semantic models, certified datasets, data dictionaries, metadata, lineage, data-quality monitoring, Agile delivery, analytics product management, model governance, or responsible AI.

· Graduate degree or relevant professional certification.