Data & Analytics Lead Consultant

And for more than 90 years, our innovative drive has kept us a step ahead of our customers' evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection. Leads complex data and analytics initiatives that deliver trusted, secure, and scalable enterprise data capabilities. This role combines technical expertise, business knowledge, and cross‑functional leadership to advance data strategy, governance, quality, modernization, and analytics across the enterprise. The Data & Analytics Lead Consultant provides strategic and technical leadership to deliver enterprise data and analytics capabilities that support business goals and enable trusted, data‑driven decision making. This role combines strong data and analytics expertise with business knowledge to lead complex initiatives, establish scalable solutions and standards, and foster collaboration across business, technology, analytics, and data governance teams. The Lead Consultant will contribute to enterprise data strategy across Data Governance & Quality, Analytics Ecosystem, Master Data Management, and Data Information & Security, while helping modernize data platforms and engineering practices. Data & Analytics Strateg yLead complex, cross‑functional data and analytics initiatives aligned with business and enterprise data strategies. Translate business objectives and requirements into actionable data, analytics, and technology solutions. Develop frameworks, roadmaps, and implementation plans for strategic data initiatives. Identify opportunities to improve how enterprise data is collected, integrated, managed, governed, and consumed. Evaluate technical approaches and communicate recommendations, risks, dependencies, and trade‑offs to stakeholders. Help establish trusted and governed data sources that can be consistently reused across business and analytical applications. Data Solutions & ModernizationLead the design and delivery of scalable data solutions supporting analytical and business needs. Provide technical guidance for data ingestion, transformation, integration, storage, modeling, and consumption. Apply modern data technologies and frameworks such as Microsoft Fabric, Azure, Spark, Python/PySpark, SQL, Kafka, dbt, or equivalent technologies. Support modernization of legacy data platforms and processes through cloud, lakehouse, and modern data engineering patterns. Ensure data solutions meet expectations for performance, reliability, security, and operational support. Data Governance & QualityEstablish and promote practices that improve the reliability, consistency, accessibility, and quality of enterprise data. Partner with business and technology teams to define data ownership, stewardship, metadata, lineage, and quality expectations. Define and monitor data quality controls, validation rules, reconciliation processes, and key data quality metrics. Help establish trusted and governed data sources that can be consistently reused across business and analytical applications. Ensure appropriate data lifecycle, retention, privacy, and governance requirements are incorporated into data solutions. Enable the appropriate data, platforms, and capabilities needed to conduct analysis, inform decisions, and deliver measurable business outcomes. Partner with analytics, data engineering, product, and business teams to develop integrated analytical capabilities. Promote consistent and reusable approaches to data modeling, data access, semantic definition, and analytics consumption. Identify gaps in the analytics ecosystem and recommend improvements to platforms, processes, and capabilities. Master Data ManagementSupport the development and adoption of trusted enterprise sources for key business data. Establish processes and standards that improve the consistency, quality, and usability of shared data across business domains. Partner with data owners, data custodians, technology teams, and business stakeholders to establish authoritative data definitions and ownership. Identify opportunities to reduce duplication and inconsistencies across enterprise data assets. Data Information & SecurityPartner with security, governance, and technology teams to protect enterprise data through appropriate security and access controls. Ensure data solutions align with applicable privacy, security, regulatory, and enterprise requirements. Incorporate security considerations into data architecture, integration, storage, and consumption designs. Promote appropriate data classification and access practices throughout the data lifecycle. Lead integrated, multi‑track projects and initiatives, ensuring high‑quality deliverables, effective risk management, and alignment with business objectives. Develop project plans, establish controls, track performance, manage dependencies, and communicate risks and status. Collaborate across business units and technology teams to resolve complex data and delivery challenges. Foster enterprise‑wide collaboration and alignment across data engineering, analytics, architecture, governance, security, and business teams. Translate complex technical concepts into clear business implications, capabilities, risks, and recommendations. Mentor team members and promote knowledge sharing and adoption of data and analytics best practices.