AVP of Enterprise Business Intelligence & Insights

Base Salary Range USD $150,674.69 - USD $195,950.45 /Yr. Join Mariner Finance! Since 1927, the Mariner Finance family of companies has provided customers with creative, flexible, and convenient lending options. Headquartered in Baltimore, Mariner Finance operates coast-to-coast with physical locations in over half the states. With a growing number of employees, superior customer service remains the cornerstone of our business, and we pride ourselves in delivering a variety of loans with an enhanced focus on exceptional service. We work with customers to find options that are beneficial to their specific needs, which is why we are recognized by our customers as one of the community’s consumer finance companies of choice. Benefits: For information regarding our benefits, please visit: https://www.marinerfinance.com/careers/benefits/  All full time employees are provided with a generous benefits package in addition to their monetary compensation. Learn more about it today. Job Details In this role, you will... Lead the enterprise Business Intelligence and Analytics Engineering function within the Data organization, setting the technical vision, standards, and operating model for the final-mile semantic data layer that connects governed, curated data products to business-ready metrics, dashboards, and AI-enabled insights across Mariner. Bring deep, hands-on expertise in big data, cloud, and modern data platforms (Databricks, Snowflake) and a track record of using AI to accelerate code and semantic model generation. Serve as the enterprise technical leader for semantic layer architecture, analytics engineering practices, and BI delivery, partnering with Data, Technology, and business leadership to translate large-scale, complex data — including experience gained delivering enterprise data solutions within fintech or major financial services organizations — into trusted, business-facing insights. Advance Mariner’s analytics engineering and BI maturity by building scalable semantic models, dashboards, and AI-enabled insight capabilities, and by guiding enterprise-wide adoption of modern big data, cloud, and AI technologies. Responsibilities and Duties: Own the enterprise semantic layer and final-mile data architecture that connects governed, curated data products to business-ready metrics, dashboards, and AI-enabled insights. Lead the design and build-out of scalable semantic models, metric layers, and reusable data marts on modern cloud and big data platforms (Databricks, Snowflake) that power enterprise BI, analytics, and AI use cases. Set the technical strategy and standards for analytics engineering, including data modeling, transformation pipelines, metric definitions, and semantic tooling across the enterprise data stack. Champion the adoption of AI and LLM-based tools across the BI and analytics engineering function, including using AI to accelerate code generation, semantic model and metric generation, documentation, and dashboard development. Partner with Data Engineering, Platform, and Technology leadership to ensure semantic and BI layers are built on trusted, governed, high-quality data pipelines across cloud and big data environments. Lead the development of executive dashboards, scorecards, and AI-enabled business insights that translate complex technical and data work into clear, actionable recommendations for senior business leaders. Serve as the enterprise technical authority on BI architecture, semantic layers, reporting data structures, and analytics engineering best practices, driving consistency and reuse across business domains. Guide the use of modern big data, cloud, and analytics engineering technologies, including Databricks, Snowflake, SQL, Python, ETL/ELT frameworks, Tableau, Power BI, and semantic modeling tools. Act as a senior, business-facing advisor to executive and technology stakeholders, translating technical roadmaps and data strategy into business value, ROI, and decision support. Build, lead, and grow a high-performing team of BI and analytics engineering professionals, developing technical depth alongside strong stakeholder partnership skills. Lead the roadmap for enterprise semantic layers, dashboards, and AI-enabled insights, balancing technical scalability, governance, and business and executive priorities. Drive consistency and reusability across the semantic and BI layer by promoting common data definitions, governed metrics, and enterprise data modeling standards. Establish intake, prioritization, and delivery processes for enterprise BI, semantic layer, and analytics engineering initiatives, ensuring quality, production support, and stakeholder adoption. Responsible for managerial matters for direct reports, including performance appraisals, goal setting, coaching, development planning, promotions, salary recommendations, staffing decisions, and terminations in accordance with the company hiring process, personnel policies, and budget requirements Perform additional duties as needed to support Data organization, enterprise BI, and business needs. Required Qualifications: Bachelor’s degree in Data Analytics, Business Analytics, Information Systems, Computer Science, Engineering, Statistics, Finance, or a related field; additional, applicable years of experience may be substituted for a bachelor’s degree. Minimum of ten (10) years of progressively responsible experience in big data engineering, analytics engineering, business intelligence, or related data solutions, with demonstrated depth in large-scale data environments. Minimum of three (3) years of leadership experience, including responsibility for leading teams, matrixed resources, enterprise-level analytics, BI, or data engineering initiatives. Demonstrated experience building and owning final-mile semantic data layers — the layer that connects curated and gold data products to business-ready metrics, dashboards, and downstream con