Data & Analytics Lead Consultant

At Allstate, great things happen when our people work together to protect families and their belongings from life’s uncertainties. 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.  Job Description 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. Key Responsibilities: Data & Analytics Strateg y • Lead 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. • Contribute to functional strategy and define measurable success criteria for enterprise-wide initiatives. • 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. Data Solutions & Modernization • Lead 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. • Promote reusable patterns and standards that improve consistency, scalability, maintainability, and delivery efficiency. • Ensure data solutions meet expectations for performance, reliability, security, and operational support. Data Governance & Quality • Establish 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. Analytics Ecosystem • Enable the appropriate data, platforms, and capabilities needed to conduct analysis, inform decisions, and deliver measurable business outcomes. • Partner with analytics, data engineering, product