Lead Business Intelligence Analyst

Job Summary The Advisory Business Intelligence & Analytics professional serves as a strategic individual contributor within the eMoney Data & Analytics organization, acting as a trusted advisor to business leaders and cross-functional stakeholders. This role is responsible for translating complex business challenges into enterprise analytics strategies, delivering actionable insights, and enabling data-informed decision making across the organization. This role partners closely with business executives, product leaders, technology teams, subject matter experts, and external partners to identify opportunities where analytics can accelerate business outcomes. Beyond delivering insights, this role influences the evolution of the organization's analytical capabilities by guiding analytics architecture, defining enterprise measurement frameworks, promoting data governance best practices, and championing a culture of data-driven decision making. This position plays a key role in shaping and advancing the enterprise analytics ecosystem through scalable, governed, and reusable analytics solutions. The Advisory BI Analyst partners across business and technology teams to develop semantic models, data products, metrics, reporting standards, self-service capabilities, and reusable analytical assets that create a consistent and scalable foundation for business intelligence and decision support. This role evaluates and incorporates emerging AI and advanced analytics capabilities into the enterprise analytics strategy, ensuring responsible adoption of generative AI, predictive analytics, and intelligent automation to improve business decision making and analytical productivity. Job Responsibilities •    Serve as a trusted advisor to executive leadership by translating strategic business objectives into enterprise analytics strategies and solutions that drive measurable business outcomes. •    Influence enterprise decision making through advanced analytics, executive-level storytelling, and actionable insights that improve business performance, customer outcomes, and operational efficiency. •    Identify opportunities to accelerate business growth, productivity, customer experience, and digital transformation through innovative use of data, analytics, and AI. •    Lead the design and evolution of enterprise analytics solutions, partnering with business, technology, and data teams to promote scalable, secure, and reusable business intelligence capabilities. •    Influence and promote architectural standards for semantic models, data products, metric definitions, dashboard architecture, metadata, lineage, self-service analytics, and analytical asset lifecycle management to support consistency, scalability, and long-term maintainability. •    Develop enterprise measurement frameworks, key performance indicators (KPIs), forecasting models, and performance reporting strategies that align analytics with organizational objectives. •    Create reusable analytics frameworks, design patterns, and accelerators that standardize solution development, improve maintainability, and reduce duplication across business domains. •    Ensure analytical solutions align with enterprise architecture, data governance, security, privacy, and data management standards while supporting evolving business priorities. •    Evaluate and recommend AI-enabled analytics capabilities, including generative AI, predictive analytics, automated insights, natural language querying, and intelligent decision support solutions that enhance business outcomes. •    Promote responsible AI practices by ensuring analytics solutions align with governance, compliance, security, and risk management standards. •    Provide strategic thought leadership by identifying emerging business trends, risks, technologies, and opportunities that influence enterprise analytics strategy and long-term planning. •    Lead enterprise analytics initiatives from strategy and solution design through implementation, adoption, and value realization, ensuring delivery of scalable, business-focused outcomes. •    Partner with business leaders to define outcome-based success measures, quantify realized value, and ensure analytics investments deliver measurable business, operational, customer, and financial outcomes. •    Drive enterprise-wide adoption of data-informed decision making by promoting analytics best practices, increasing data literacy, and fostering a culture of continuous improvement. •    Provide thought leadership by driving alignment on analytics priorities, influencing strategic roadmaps, and recommending best practices that strengthen organizational decision-making capabilities. •    Mentor analytics practitioners through technical leadership, knowledge sharing, architectural guidance, and promotion of best practices in analytics and data storytelling. Requirements •    Bachelor’s degree in mathematics, Statistics, Computer Science, Data Analytics, Business, Economics, or another quantitative discipline; Master's degree preferred or an equivalent combination of education and experience. •    10+ years of progressive experience in business intelligence, analytics, data strategy, management consulting, or related advisory roles, including experience leading enterprise-scale analytics initiatives and influencing senior business and technology leaders. •    Demonstrated success partnering with executive leadership to shape business strategy, prioritize investments, and deliver measurable business outcomes through data, analytics, and AI. •    Experience leading enterprise-wide transformation initiatives involving analytics modernization, KPI standardization, self-service analytics, data governance, data products, or AI-enabled decision support capabilities. •    Experience operating within complex, cross-functional organizations and influencing outcomes without direct managerial authority. •    Financial services, wealth management, fintech, or other highl