VP Lending Data Engineering & Analytics Technology

This is a senior technology and data leadership role responsible for the design, development, and enhancement of data and analytics capabilities supporting Wealth Lending Servicing platforms. The role brings together deep expertise in data engineering, analytics, and enterprise integration to deliver scalable, resilient solutions aligned with business objectives and the target‑state Wealth Lending technology architecture.

The individual acts as a bridge between business and technology, translating operational, risk, and regulatory requirements into high‑quality data solutions that support the global end‑state Lending Servicing platform.

Responsibilities

• Analyze Wealth Lending Servicing data to deliver actionable insights supporting business, operations, risk, and regulatory reporting needs.
• Own definition, calculation, and validation of key Lending metrics and KPIs to ensure consistency across platforms and reports.
• Design and maintain logical and physical data models, translating business and regulatory requirements into clear data and analytical specifications.
• Partner with application, platform, and integration teams to deliver scalable, resilient data pipelines and analytical solutions.
• Ensure data quality, integrity, reconciliation, and exception handling across end‑to‑end Lending Servicing data flows.
• Maintain end‑to‑end data lineage and traceability, ensuring compliance with enterprise architecture and regulatory standards.
• Act as a bridge between business, product, operations, risk, compliance, and technology teams to align data solutions with business intent.
• Contribute as a senior data lead in Agile delivery teams, defining data stories, validating outputs, and driving timely execution.
• Proactively identify data issues and improvement opportunities, driving remediation to enhance platform reliability and data transparency.
• Influence stakeholders through clear, data‑driven communication and well‑reasoned analytical recommendations.

Qualifications

• 10–15 years of experience in Financial Services, with a strong focus on data analytics, data engineering, and technology delivery within complex, regulated environments.
• Proven experience delivering Lending or Credit domain data solutions, preferably across servicing, payments, statements, risk, or regulatory reporting.
• Solid understanding of RDBMS (SQL, PL/SQL) with knowledge in NoSQL databases (e.g., Cassandra, MongoDB, DynamoDB).
• Solid experience in data modeling (conceptual, logical, and physical), including definition of metrics, hierarchies, and business rules to support analytics and reporting.
• Experience designing and delivering end‑to‑end data solutions across multiple systems, including source‑to‑target mappings, data pipelines, and downstream consumption (reports, dashboards, extracts).
• Strong understanding of data governance, data quality controls, lineage, reconciliation, and regulatory reporting requirements in a banking environment.
• Familiarity with distributed data platforms, databases, and integration patterns; experience with Java-based systems is a plus but not mandatory.
• Ability to translate business, risk, and regulatory requirements into clear analytical specifications, data structures, and actionable insights.
• Experience working in Agile delivery models, collaborating closely with Product, Operations, Risk, and Technology stakeholders.
• Demonstrated ability to document data designs, analytical logic, lineage, and control frameworks in line with enterprise and regulatory standards.
• Strong communication and influencing skills, with the ability to present data-driven insights and recommendations to senior stakeholders.

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