Senior Vice President, Data Transformation & Product Strategy

📍 Job Overview

Job Title: Senior Vice President, Data Transformation & Product Strategy

Company: BNY Mellon

Location: New York, NY, United States

Job Type: Full-time

Category: Data Strategy & Transformation / Product Management

Date Posted: November 2, 2026

Experience Level: 10+ Years

Remote Status: On-site

🚀 Role Summary

• Lead the strategic transformation of enterprise data from a fragmented state into a cohesive, operational backbone for client and account information, aligning with BNY Mellon's "Single Front Door" initiative for enterprise onboarding.

• Define and execute a comprehensive product vision, strategy, and roadmap for enterprise data solutions, focusing on reusable data services, streamlined onboarding workflows, and robust governance controls.

• Drive the productization of analytics and AI-ready capabilities, ensuring data is authoritative, consistent, and accessible across critical applications and end-to-end workflows to enhance decision-making and operational efficiency.

• Orchestrate cross-functional delivery teams, including Product, Engineering, Architecture, Operations, Governance, and Risk, to ensure successful implementation and adoption of enterprise data initiatives.

• Identify and implement opportunities for process simplification, automation expansion, and scalability improvements to reduce duplication and enhance operational resilience and control effectiveness.

📝 Enhancement Note: This role sits at the intersection of Data Strategy, Product Management, and Operations Transformation, requiring a leader who can translate complex data challenges into actionable product roadmaps and drive large-scale change within a financial services organization. The emphasis on "operational backbone" and "workflow transformation" indicates a strong need for someone with a deep understanding of how data directly impacts business processes and operational efficiency.

📈 Primary Responsibilities

• Define and execute the product vision, strategy, roadmap, prioritized capabilities, requirements, and measurable outcomes for enterprise data solutions, with a focus on client and account data.

• Productize reusable data services, onboarding workflows, governance controls, and analytics- and AI-ready capabilities to foster standardization and efficiency.

• Orchestrate cross-functional delivery across Product, Engineering, Architecture, Operations, Governance, Risk, and business stakeholders, ensuring alignment and accountability.

• Own scope, sequencing, dependencies, risks, release readiness, adoption, and stakeholder accountability across strategic, enterprise-wide initiatives.

• Identify and deliver opportunities to eliminate duplication, simplify processes, expand automation, and improve scalability and operational efficiency across data-centric workflows.

• Drive adoption of enterprise data capabilities by embedding authoritative data into critical applications and end-to-end workflows that power the firm’s decisions and operations.

• Establish and reinforce common data standards, reusable patterns, and platform commitments that support enterprise-wide consistency and scale, moving away from fragmented local views.

• Partner with stakeholders across business origination, onboarding, account setup, billing, and downstream applications to ensure product strategy aligns with business priorities, operational needs, control requirements, and long-term enterprise value creation.

• Track and measure business outcomes, adoption rates, and value realization from enterprise data investments, demonstrating ROI and impact.

📝 Enhancement Note: The responsibilities highlight a blend of strategic product leadership and hands-on execution oversight, common for senior roles driving transformation. The emphasis on "productize reusable data services" and "embedding authoritative data" signifies a shift towards treating data as a product and integrating it seamlessly into operational processes, a key trend in modern data management and operations.

🎓 Skills & Qualifications

Education:

• Bachelor’s degree or equivalent professional experience in a relevant field such as Computer Science, Data Science, Information Management, Business Administration, or a related discipline. Experience:

• 10+ years of progressive experience in product management, data product strategy, enterprise data transformation, technology delivery, or a closely related discipline, preferably within the financial services sector.

• Demonstrated success translating complex business and data needs into actionable product roadmaps, detailed requirements, scalable operating models, and comprehensive implementation plans.

• Proven ability to lead complex, cross-functional delivery efforts, effectively navigate competing priorities, and influence senior stakeholders and executive leadership.

• Strong command of enterprise data platforms, data integration patterns, data governance frameworks, data quality management, data access controls, and the principles of reusable data products. Required Skills:

• Product Vision & Strategy: Ability to define and articulate a compelling product vision, strategy, and roadmap for enterprise data solutions.

• Data Transformation Leadership: Proven experience leading large-scale data transformation initiatives, migrating from fragmented systems to integrated platforms.

• Enterprise Data Management: Deep understanding of master data management (MDM), data governance, data lineage, data quality frameworks, and data architecture principles.

• Cross-functional Orchestration: Exceptional ability to lead and coordinate diverse teams (Product, Engineering, Operations, Risk, Governance) to achieve common goals.

• Stakeholder Management & Influence: Demonstrated skill in influencing senior executives and managing diverse stakeholder expectations.

• Analytical & Execution Skills: Strong analytical capabilities to assess complex problems and execute solutions efficiently and effectively.

• Change Leadership: Proven ability to drive organizational change, adoption, and embed new processes and technologies.

Preferred Skills:

• Experience in financial services, particularly within onboarding platforms, client data management, master or reference data, advanced analytics, automation, or AI enablement.

• Experience with product operating models, Agile or SAFe delivery methodologies, KPI/OKR design, adoption measurement frameworks, and enterprise controls.

• Working knowledge of modern data architecture, API design, integration patterns, analytics platforms, and contemporary data technologies.

📝 Enhancement Note: The experience requirements are substantial, indicating a need for a seasoned leader. The emphasis on "translating complex business and data needs" suggests that candidates should be adept at bridging the gap between technical capabilities and business outcomes. The preferred skills point towards a candidate who is not only strategic but also possesses a good understanding of the technical underpinnings and modern delivery methodologies.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Data Strategy Case Studies: Examples demonstrating the development and execution of enterprise data strategies that led to significant improvements in data quality, accessibility, or business insights.

• Product Roadmap Development: Evidence of creating and managing product roadmaps for data platforms or data-centric products, showcasing prioritization, sequencing, and dependency management.

• Workflow Optimization Examples: Demonstrations of how you've identified and simplified complex business workflows, particularly in areas like client onboarding, account setup, or data integration, leading to measurable efficiency gains.

• System Implementation & Adoption: Case studies detailing the implementation of enterprise data solutions or platforms, including strategies for driving adoption and user engagement.

• ROI & Value Realization: Projects where you have clearly defined and measured business outcomes, adoption rates, and value realization from data investments, showcasing impact on productivity, control, or revenue.

Process Documentation:

• Workflow Design & Optimization: Showcase experience in designing and documenting end-to-end workflows, with a focus on identifying bottlenecks, redundancies, and opportunities for automation and simplification in data-intensive processes.

• Data Governance Frameworks: Evidence of establishing or significantly contributing to data governance frameworks, including standards, policies, and procedures for data quality, lineage, and access control.

• Platform & Service Enablement: Examples of how you've defined reusable data services or platform capabilities that were documented and made available for consumption by other applications or teams.

• Performance Measurement & Reporting: Documentation of how key performance indicators (KPIs) and objectives and key results (OKRs) were established, tracked, and reported on for data initiatives to measure success and drive continuous improvement.

📝 Enhancement Note: For a role at this seniority, a robust portfolio is crucial. It should not just list past projects but demonstrate a strategic approach to data transformation, product development, and process optimization. The focus on "reusable data services," "single front door," and "operational backbone" implies a need for portfolio pieces that highlight scalable, integrated solutions.

💵 Compensation & Benefits

Salary Range:

• The estimated base salary range for this Senior Vice President role in New York, NY, is approximately $170,000 - $250,000 USD per year.

• This estimate is based on market data for senior leadership positions in financial services and technology in the New York City metropolitan area, considering the extensive experience required (10+ years) and the strategic nature of the role. BNY Mellon's stated practice of assessing market data for competitive compensation further supports this range. Benefits:

• Comprehensive Health Coverage: Includes medical, dental, and vision insurance plans for employees and eligible dependents.

• Retirement Savings: Eligibility for a 401(k) plan to support long-term financial planning.

• Financial Incentives: Potential eligibility for an annual discretionary incentive award, reflecting performance-based compensation.

• Paid Time Off: Generous paid leaves, including vacation time, sick time, and paid volunteer time to support work-life balance and community engagement.

• Life Insurance: Basic life insurance coverage provided for employees.

• Wellbeing Programs: Access to wellbeing programs and resources designed to foster personal resilience and overall health.

• Professional Development: Opportunities for continuous learning and growth within a leading financial institution.

Working Hours:

• Typically 40 hours per week, aligning with standard full-time employment in the financial services industry. However, given the senior leadership and transformation nature of the role, flexibility and availability beyond standard hours may be expected to meet project deadlines and critical business needs.

📝 Enhancement Note: The salary range is an estimation based on industry benchmarks for a Senior Vice President role in a major financial hub like New York, with a strong emphasis on data strategy and transformation. The provided benefits are based on typical offerings for large financial institutions and BNY Mellon's stated benefit philosophy.

🎯 Team & Company Context

🏢 Company Culture

Industry: Financial Services (specifically, investment banking, asset management, and financial technology services). BNY Mellon is a key player in the global financial system, influencing a significant portion of the world's investible assets.

Company Size: Large Enterprise (BNY Mellon is a global financial institution with tens of thousands of employees worldwide). This size implies complex organizational structures, extensive resources, and significant impact.

Founded: BNY Mellon has a rich history, with its predecessor institutions dating back to 1784. This longevity suggests a culture that values stability, long-term vision, and deep industry expertise, while also adapting to modern technological advancements.

Team Structure:

• The role is within the "Data Solutions and Services Platform" and focuses on enterprise-wide data transformation.

• This implies a matrixed structure where the SVP will orchestrate delivery across various established departments: Product Management, Engineering, Architecture, Operations, Data Governance, Risk Management, and business units responsible for origination, onboarding, and downstream applications.

• The team will likely be composed of product managers, data architects, engineers, business analysts, and operations specialists, reporting to various functional leaders but collaborating under the SVP's strategic direction. Methodology:

• Data-Driven Transformation: The core methodology revolves around leveraging data as a strategic asset to drive business outcomes, enhance client experience, and improve operational resilience.

• Product-Centric Approach: Treating data and onboarding workflows as "products" to be developed, managed, and iterated upon, with a focus on reusable services and clear platform commitments.

• Agile & Scalable Delivery: While not explicitly stated for this SVP role, the underlying teams are likely to employ Agile or SAFe methodologies for efficient, iterative delivery of capabilities and features.

• Cross-Functional Collaboration: A strong emphasis on breaking down silos and fostering collaboration between technical, operational, and business stakeholders to achieve a unified vision.

Company Website: https://www.bnymellon.com/

📝 Enhancement Note: BNY Mellon's positioning as a "leading global financial services company at the heart of the global financial system" underscores the scale and importance of this role. The company's emphasis on "cutting-edge AI and breakthrough technologies" suggests a forward-thinking culture, even within a traditional industry. The mention of "innovators" and "bold ideas" indicates an environment that values proactive problem-solving and strategic thinking.

📈 Career & Growth Analysis

Operations Career Level: This is a Senior Vice President (SVP) level role, placing it at a very senior executive leadership tier. It signifies significant responsibility for strategic direction, large-scale transformation, and P&L or significant budget oversight (though not explicitly stated for this role, it's common at this level). The focus is on defining and executing enterprise-wide strategies that have a direct impact on operational efficiency and product strategy.

Reporting Structure: While not explicitly detailed, an SVP typically reports to an Executive Vice President (EVP) or a C-suite executive (e.g., Chief Data Officer, Chief Technology Officer, or Head of Operations/Strategy). The SVP will, in turn, lead and influence multiple cross-functional teams and direct reports.

Operations Impact: The role's primary objective is to transform BNY Mellon's operational backbone by creating a unified enterprise data platform and a strategic "Single Front Door" for onboarding. This has a profound impact on:

• Client Experience: Enabling a connected view of client information leads to smoother interactions.

• Operational Resilience & Control: Standardized, authoritative data enhances data integrity, reduces errors, and strengthens compliance.

• Productivity: Eliminating duplication and simplifying processes drives efficiency for internal teams.

• Innovation: Providing analytics- and AI-ready data capabilities unlocks opportunities for new products, services, and predictive analytics.

• Return on Investment: Optimizing data assets and processes directly contributes to better returns on the company's data investments.

Growth Opportunities:

• Strategic Leadership: Opportunity to shape the future of data and product strategy for a global financial institution, influencing critical business decisions.

• Transformational Impact: Lead a high-visibility, mission-critical transformation that will redefine how BNY Mellon operates and serves its clients.

• Cross-Functional Expertise: Deepen expertise by working across Product, Engineering, Architecture, Operations, Governance, and Risk, gaining a holistic view of the enterprise.

• Innovation & Technology: Drive the adoption of advanced technologies like AI and automation, staying at the forefront of industry innovation.

• Executive Visibility: Direct engagement with senior leadership, providing opportunities for mentorship and career advancement within BNY Mellon.

📝 Enhancement Note: The SVP title indicates a role with significant strategic influence and potential for further executive advancement. The "Data Transformation" aspect means this role is central to BNY Mellon's modernization efforts, offering a chance to make a lasting impact and build a strong track record for future leadership roles.

🌐 Work Environment

Office Type: This role is designated as "On-site" and is based in BNY Mellon's offices in Lake Mary, FL, with a specific address provided for New York, NY. This suggests a hybrid model where the primary base might be one location, but significant engagement or leadership may also involve presence in other key operational hubs. The explicit mention of Lake Mary, FL, suggests a potential operational center for data services.

Office Location(s):

• Primary stated location: Lake Mary, FL (mentioned in the initial description).

• Provided address: 240 Greenwich Street, New York, NY 10286. This duality suggests the role may require travel or split time between these key locations, or that the role has significant stakeholders in both regions.

• Global Presence: As a global financial institution, BNY Mellon has offices worldwide, implying that stakeholders and project impacts may extend beyond these specific locations.

Workspace Context:

• Collaborative Environment: The role demands extensive cross-functional collaboration, suggesting a workspace designed to facilitate team interaction, brainstorming, and problem-solving sessions. This likely includes meeting rooms, project spaces, and open-plan areas.

• Technology-Rich: As a leader in data transformation and product strategy, the workspace will be equipped with advanced technology infrastructure, including high-speed connectivity, powerful workstations, and access to sophisticated data analytics and visualization tools.

• Data-Centric Focus: The environment will be geared towards data analysis, strategic planning, and product development, fostering a culture of innovation and continuous improvement in data management.

Work Schedule:

• Standard working hours are expected to be around 40 hours per week. However, as an SVP leading a critical transformation, significant flexibility and dedication beyond typical business hours will likely be required to manage project timelines, stakeholder engagement across time zones, and address urgent operational issues.

📝 Enhancement Note: The on-site requirement, coupled with mentions of both Florida and New York locations, indicates a need for flexibility and potentially travel. This is typical for senior roles overseeing distributed teams or critical operational hubs. The emphasis on collaboration suggests an office environment that supports team dynamics.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A review of your resume and application, focusing on the depth and breadth of your experience in enterprise data transformation, product leadership, and financial services.

• Hiring Manager Interview: A discussion with the direct hiring manager to assess your strategic thinking, leadership style, and alignment with the role's core responsibilities.

• Cross-Functional Panel Interviews: Interviews with key stakeholders from Product, Engineering, Architecture, Operations, Governance, and business units. These sessions will evaluate your ability to collaborate, influence, and drive consensus across diverse teams. Expect questions related to data strategy, product roadmapping, change management, and stakeholder engagement.

• Executive-Level Interview: A final interview with a senior executive (e.g., EVP or C-suite) to assess your executive presence, strategic vision, and overall fit for leading a critical enterprise transformation.

• Case Study/Presentation (Potential): You may be asked to prepare a presentation or case study based on a hypothetical challenge or a review of your past work, demonstrating your approach to data transformation, product strategy, and operational improvement.

Portfolio Review Tips:

• Quantify Impact: For each project in your portfolio, clearly articulate the business problem, your role, the solutions implemented, and quantifiable results (e.g., % reduction in onboarding time, % improvement in data quality, $ saved through automation, increased adoption rates).

• Showcase Strategic Thinking: Highlight how your work aligned with broader business objectives and contributed to the company's strategic goals. Demonstrate your ability to think long-term and build scalable solutions.

• Emphasize Transformation: Select examples that best illustrate your experience in leading significant transformations, moving from fragmented systems to integrated, efficient platforms.

• Demonstrate Cross-Functional Leadership: Use examples that show your ability to lead and influence diverse teams, manage complex dependencies, and gain buy-in from senior stakeholders.

• Structure for Clarity: Organize your portfolio logically, perhaps by theme (e.g., Data Strategy, Product Development, Process Optimization) or by project impact. Use clear, concise language and compelling visuals where appropriate.

Challenge Preparation:

• Data Strategy & Roadmap: Be prepared to discuss how you would approach developing an enterprise data strategy and product roadmap for a large financial institution. Consider elements like stakeholder alignment, prioritization frameworks, and technology considerations.

• Operational Efficiency: Anticipate questions about identifying and driving operational efficiencies through data and process improvements. Think about common challenges in financial services onboarding and data management.

• Change Management: Prepare to discuss your strategies for driving adoption of new data platforms, processes, and standards across a large, complex organization.

• Stakeholder Management: Practice articulating how you would manage competing priorities and build consensus among senior leaders with different objectives.

📝 Enhancement Note: The interview process for an SVP role will be rigorous and multi-faceted, focusing heavily on strategic leadership, proven transformation experience, and stakeholder influence. A well-curated portfolio that clearly demonstrates quantifiable impact and strategic thinking is essential.

🛠 Tools & Technology Stack

Primary Tools (Implied):

• Data Governance & Quality Tools: Experience with platforms for data cataloging, lineage tracking, data quality monitoring, and policy enforcement (e.g., Informatica, Collibra, Talend Data Fabric, IBM InfoSphere).

• Master Data Management (MDM) Platforms: Familiarity with MDM solutions for creating and managing authoritative data sources (e.g., Informatica MDM, Oracle MDM, SAP MDG, Reltio).

• Data Integration & ETL Tools: Proficiency with tools for moving and transforming data between systems (e.g., Informatica PowerCenter, Talend, IBM DataStage, Microsoft SSIS, AWS Glue, Azure Data Factory).

• API Management Platforms: Understanding of how to manage and expose data services via APIs (e.g., Apigee, MuleSoft, Azure API Management).

Analytics & Reporting:

• Business Intelligence (BI) Tools: Experience with platforms for data analysis, visualization, and dashboard creation (e.g., Tableau, Power BI, QlikView).

• Data Warehousing & Data Lake Technologies: Familiarity with cloud-based data warehouses (e.g., Snowflake, Redshift, BigQuery) and data lake concepts.

• Statistical & ML Platforms: Exposure to tools for advanced analytics and AI model development (e.g., Python libraries like Pandas, Scikit-learn; R; SAS; cloud ML platforms).

CRM & Automation:

• CRM Systems: While not the primary focus, understanding how enterprise data integrates with CRM systems (e.g., Salesforce) is beneficial for client data context.

• Workflow Automation Tools: Familiarity with platforms for automating business processes (e.g., Pega, Appian, ServiceNow, Microsoft Power Automate) could be relevant for onboarding workflow transformation.

• Project & Portfolio Management Tools: Tools used for managing large-scale initiatives and tracking progress (e.g., Jira, Confluence, Microsoft Project, Asana).

📝 Enhancement Note: While specific tools are not listed, the role's focus on enterprise data transformation, product strategy, and operational backbone implies a need for broad knowledge of data management, integration, governance, and analytics technologies. Candidates should be able to speak to their experience with enterprise-grade solutions in these areas.

👥 Team Culture & Values

Operations Values:

• Data-Driven Decision Making: A strong emphasis on using data and analytics to inform strategic decisions, measure performance, and drive continuous improvement across all operations.

• Efficiency & Scalability: A commitment to designing and implementing processes and systems that are efficient, scalable, and reduce operational overhead.

• Collaboration & Partnership: Fostering a culture where teams work together seamlessly across departments (Product, Engineering, Ops, Risk, Business) to achieve shared goals, breaking down silos.

• Innovation & Continuous Improvement: Encouraging the exploration of new technologies and methodologies to enhance data capabilities, product offerings, and operational effectiveness.

• Accountability & Ownership: A culture of taking ownership for outcomes, managing risks, and delivering on commitments with a focus on measurable results.

Collaboration Style:

• Cross-Functional Integration: The role demands a highly collaborative style, actively engaging with and influencing leaders and teams across Product, Engineering, Architecture, Operations, Governance, Risk, and various business units.

• Process Review & Feedback: Openness to constructive feedback and a proactive approach to reviewing and iterating on processes and strategies with stakeholders to ensure alignment and effectiveness.

• Knowledge Sharing: Encouraging the sharing of best practices, insights, and learnings across teams to build collective intelligence and accelerate progress on enterprise data initiatives.

• Outcome-Oriented: A shared focus on achieving defined business outcomes and delivering tangible value, rather than just completing tasks.

📝 Enhancement Note: The company culture at BNY Mellon, as described, emphasizes innovation, technology, and collaboration. For this role, the ideal candidate will embody these values, bringing a proactive, data-driven, and partnership-oriented approach to leading complex transformations.

⚡ Challenges & Growth Opportunities

Challenges:

• Fragmented Systems & Data: Overcoming the inertia of existing fragmented systems and diverse data silos to build a unified enterprise data platform requires significant strategic planning and execution.

• Organizational Change Management: Driving adoption of new data standards, processes, and platforms across a large, established financial institution can be challenging, requiring strong change leadership and stakeholder buy-in.

• Balancing Strategic Vision with Tactical Execution: Ensuring the long-term strategic vision for data transformation is translated into achievable, prioritized steps with clear outcomes requires constant focus and effective resource management.

• Navigating Competing Priorities: Aligning diverse business units and functional teams, each with their own priorities, towards a common enterprise data strategy requires exceptional negotiation and influence skills.

• Measuring Complex ROI: Quantifying the return on investment for broad data transformation initiatives, which often yield benefits in terms of efficiency, resilience, and future innovation, can be complex.

Learning & Development Opportunities:

• Deepening Financial Services Data Expertise: Gaining in-depth knowledge of the specific data challenges and opportunities within the institutional asset and commercial hub sectors of BNY Mellon.

• Advanced Data & AI Strategy: Opportunities to lead and implement cutting-edge data strategies, including advanced analytics, AI enablement, and data monetization initiatives.

• Executive Leadership Development: Exposure to top-tier executive leadership, providing mentorship and development in strategic decision-making, enterprise-level governance, and large-scale organizational leadership.

• Industry Best Practices: Staying abreast of and implementing leading practices in enterprise data management, product strategy, and digital transformation within the financial services sector.

• Building a Transformational Legacy: The opportunity to leave a lasting impact on BNY Mellon's operational capabilities and strategic direction through successful data transformation.

📝 Enhancement Note: This role presents significant challenges due to its transformative nature within a large enterprise. However, these challenges are directly linked to substantial growth and learning opportunities for a seasoned leader.

💡 Interview Preparation

Strategy Questions:

• "Describe your approach to defining an enterprise data strategy for a global financial institution. What are the key components, and how would you ensure alignment with business objectives and operational needs?" (Focus on structured approach, stakeholder engagement, measurable outcomes).

• "How would you prioritize capabilities for a new enterprise data platform or onboarding workflow? Walk us through your decision-making framework." (Highlight frameworks like RICE, MoSCoW, or value/effort matrices, and how you incorporate risk and operational impact).

• "Imagine you've launched a new enterprise data service, but adoption is low. What steps would you take to diagnose the issue and drive adoption?" (Emphasize understanding user needs, communication strategies, training, and iterative feedback loops). Company & Culture Questions:

• "Based on your understanding of BNY Mellon, what do you see as the biggest data-related challenges and opportunities for the firm, and how would your role address them?" (Research recent BNY Mellon news, strategic initiatives, and industry trends).

• "Describe a time you had to lead a significant change initiative across multiple departments with competing priorities. How did you manage stakeholder relationships and ensure alignment?" (Prepare a STAR method response focusing on influence, communication, and conflict resolution).

• "How do you foster a culture of data-driven decision-making and continuous improvement within your teams and across the organization?" (Discuss metrics, reporting, feedback loops, and empowering teams). Portfolio Presentation Strategy:

• "Elevator Pitch" for Key Projects: Be ready to summarize your most impactful projects in 1-2 minutes each, focusing on the problem, your solution, and the quantifiable business outcome.

• Deep Dive on Transformation: Select one or two key projects that best demonstrate your ability to lead large-scale data transformation or product strategy implementation. Be prepared to discuss challenges, trade-offs, and lessons learned in detail.

• Data Storytelling: Use your portfolio to tell a compelling story about how you leverage data to solve business problems, drive efficiency, and enable innovation.

• Focus on "Operational Backbone": Tailor your examples to highlight how your work created foundational data capabilities that supported broader operational processes, improved control, and enabled downstream applications.

• Interactive Elements: If possible, be prepared to walk through a dashboard, a process flow diagram, or a product roadmap excerpt to illustrate your points more concretely.

📝 Enhancement Note: Interview preparation should focus on demonstrating strategic leadership, a deep understanding of data transformation challenges in financial services, and a proven ability to drive complex initiatives through cross-functional collaboration and strong stakeholder management.

📌 Application Steps

To apply for this Senior Vice President, Data Transformation & Product Strategy position:

• Submit your application through the provided Oracle Cloud portal link.

• Tailor Your Resume: Customize your resume to highlight achievements and experiences directly relevant to enterprise data transformation, product strategy, financial services, and leadership. Use keywords from the job description.

• Develop Your "Transformation" Narrative: Prepare to articulate your experience leading significant data-related transformations. Think about specific examples of moving from fragmented systems to integrated platforms, and the impact this had.

• Curate Your Portfolio: Select 2-3 of your most impactful projects that demonstrate your strategic thinking, execution capabilities, and quantifiable results in data strategy, product management, and process optimization. Be ready to present these clearly and concisely.

• Research BNY Mellon: Understand the company's mission, recent news, strategic priorities, and its role in the financial ecosystem. Consider how your role contributes to their overall goals.

• Prepare for Executive-Level Discussion: Anticipate questions about your strategic vision, leadership philosophy, and how you would approach the challenges of this role at BNY Mellon.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.