AVP of Enterprise Business Intelligence & Insights

Base Salary Range

USD $ - USD $ /Yr.

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:

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All full time employees are provided with a generous benefits package in addition to their monetary compensation. Learn more about it today.

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…