Vice President, Data Products & Analytics Engineer

MUFG•Jersey City, NJ

1d•$153,000 - $237,000•Hybrid

About The Position

The Data Management Engineering organization is executing a product‑centric data strategy to deliver trusted, business‑aligned data products that power analytics, AI enablement, and critical decisioning across the enterprise. The organization partners closely with business, technology, and other stakeholders to ensure data assets are governed, scalable, and fit for regulatory and operational use across business domains. The Vice President, Data Products & Analytics Engineer is a senior individual‑contributor reporting to the Head of Data Management Engineering. This role has broad responsibility for shaping data product strategy, assessing business requirements, defining solutions, and ensuring consistent standards across multiple data product initiatives. This role demands strong influence across business and technology organizations, with regular interaction with senior leaders to align data product roadmaps, platform architecture, and engineering execution to enterprise priorities and measurable business outcomes.

Requirements

Demonstrated success modernizing data ecosystems through cloud‑based platforms, automation, and integrated data solutions that improve data quality, accessibility, governance, and enable advanced analytics and AI‑assisted data consumption.
Proven ability to design, scale, and operate modern data architectures—including data marts, validation, and reconciliation frameworks—to enable end‑to‑end analytics and regulatory use cases.
Strong hands‑on experience with cloud‑based data platforms and modern data architectures.
Advanced SQL and strong experience with data transformation, profiling, validation, and reconciliation frameworks.
Practical understanding of AI‑enabled data access patterns (semantic layers, natural language querying, curated retrieval) in regulated environments.
Strong grounding in metadata management, lineage, data quality controls, and certification workflows.
Experience in business, data, and application architecture and process re-engineering.
Expertise in business requirements analysis, design, functional and detail design within the Banking & Financial Services sector.
Demonstrated ability to operate with senior‑level autonomy and influence across business, technology, and risk organizations.
Strong executive communication skills, with the ability to explain complex technical concepts in clear business terms. Detail-oriented, but strategic in thinking with the ability to tell a story and sell a vision.
Effective at building alignment, driving adoption, and managing competing priorities across a matrixed organization.
Product‑oriented mindset with a balanced focus on near‑term delivery, risk management, and long‑term platform sustainability.
Demonstrated ability to build consensus across business areas and other stakeholders to support new ways of thinking about capabilities.
Ability to quickly transition as priorities change.
Expert knowledge of tools & techniques including cloud platforms, programming languages, and modern software engineering practices.
Cloud data platforms such as Snowflake and AWS‑based data services.
Enterprise data governance and metadata platforms such as Collibra.
Data Virtualization platforms such as Starburst.
ETL Tools such as Informatica
BI and analytics tools such as Tableau, PowerBI, Alteryx or equivalent platforms.
Relational databases and enterprise data warehouse technologies.
Agile delivery and collaboration tools including Jira and Confluence.
10+ years of data experience in the Banking & Financial Services sector from a technology, data, and/or business operations perspective.
10+ years of experience in data management and/or data product development.
7+ years of experience in business, systems, and data architecture, and analysis.
Proven experience as a Data Engineer and/or Business Data Architect or similar role, with a focus on business value creation and enablement.
Bachelor’s degree in science, business, management, or finance-related fields.

Nice To Haves

Advanced degree is a plus.

Responsibilities

Develop and maintain strong, trust-based relationships with key stakeholders to understand their business challenges and identify how data solutions can support their objectives.
Empower business and corporate functions with robust data capabilities, ensuring clear lineage to products, services, and business processes, providing valuable data insights within the business context, and facilitating seamless data access.
Optimize data product lifecycle management to drive modernization and value from our data assets. Identify process and procedural optimizations to advance data governance, management, and use.
Proactively engage with data users to drive data maturity, adoption, and self-service. Facilitate a culture of continuous improvement and data systems thinking.
Partner with senior business stakeholders to understand strategic objectives and ensure data products enable analytics, reporting, and data consumption challenges.
Contributes to the technical and product direction for a portfolio of well‑formed enterprise data products, translating complex business processes into curated, reusable, and governed data assets.
Provide expertise on the end‑to‑end data product lifecycle, including data sourcing, design, engineering, quality, certification, and consumption readiness.
Translate business and analytics requirements into clear data engineering specifications, and implementation plans. Apply modern data architecture patterns to enable scalable data consumption.
Collaborate across engineering and analytics teams to promote common standards, tooling, and delivery practices in a matrixed environment.
Enable advanced data consumption capabilities, including BI, self‑service analytics, and AI‑assisted querying under governed access controls.
Contribute to data literacy and adoption by supporting documentation, data catalogs, and enablement of business data users.