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 consumption.

• Strong, hands-on technical expertise in cloud and big data platforms, including Databricks and Snowflake, along with SQL, Python, and modern ETL/ELT frameworks.

• Demonstrated adoption and practical use of AI and LLM tools to accelerate code generation, semantic model and metric generation, documentation, or analytics engineering workflows.

• Experience delivering enterprise BI, analytics engineering, or data platform capabilities within fintech, banking, or another major financial services organization.

• Strong knowledge of BI and semantic architecture, including semantic layers, semantic tables/models, data marts, reporting data structures, and curated datasets that support enterprise analytics.

• Experience partnering with Data Engineering, Platform, Governance, and business leadership to align semantic and BI solutions with enterprise data strategy and data quality expectations.

• Experience with BI and visualization tools such as Tableau or Power BI, including dashboard design and stakeholder adoption.

• Ability to lead enterprise roadmaps for semantic layers, analytics engineering, and BI, balancing technical scalability with business priorities.

• Strong communication, executive presentation, and stakeholder management skills, with the ability to translate complex technical and data concepts into clear business recommendations.

• Strong leadership, coaching, and organizational skills, with the ability to lead through ambiguity and drive alignment across cross-functional technical and business teams.

Preferred Qualifications:

• Master’s degree.

• Experience in a senior or AVP-level leadership role within a major fintech, bank, or financial services data organization.

• Experience designing AI-enabled semantic layers, natural language analytics, or AI insight agents on top of governed data products.

• Experience with modern data engineering frameworks (e.g., dbt, Airflow, Spark) in addition to Databricks and Snowflake.

• Experience working with data governance tools, metadata management tools, data catalogs, or lineage platforms.

• Experience managing vendor or platform relationships across BI, cloud data, and analytics engineering tools.

Hours of Work:

Work hours will depend on the business hours of the time zone serviced. To the extent permitted by law, the Company may, in its sole discretion, change the work schedule to address business needs.

Physical Demands:

While performing the duties of this job, the employee is frequently required to sit for extended periods; reach with hands and arms; and talk or hear. The employee is occasionally required to move about. The employee must occasionally lift and/or move up to twenty (20) pounds. Specific vision abilities required by this job include close vision and the ability to adjust focus.

EEO:

Mariner Finance is an Equal Opportunity Employer and does not discriminate on the basis of race, color, religion, creed, sex, gender, gender identity or expression, marital status, age, religion, national origin, sexual orientation, familial or caregiver status, citizenship status, status as a victim of domestic violence, medical condition, genetic information, pregnancy, physical or mental disability, or status as a disabled or Vietnam era veteran. Employee must be able to perform the essential duties/functions of the position satisfactorily and, if requested, reasonable accommodations will be made to enable employees with disabilities to perform the essential duties/functions of their job, absent undue hardship. Drug/Alcohol/Smoke-free workplace.

This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee. Duties, responsibilities, and activities may change or new ones may be assigned at any time or without notice.