Data Architecture & Engineering - Senior - Financial Services - Consulting - NYC, Charlotte, Dallas

Data Architecture & Engineering - Senior - Financial Services - Consulting - NYC, Charlotte, Dallas

Location:

New York, Charlotte, Dallas.

At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.

Senior Consultant – Financial Services - Data & Analytics – Data Architecture and Engineering

EY is the only professional services firm with a dedicated business unit (“FSO”) that serves the financial services marketplace. Our FSO teams have led the transformation of the industry. If you thrive on solving complex challenges, come join our dynamic team.

Data is yet to be utilized to its fullest potential. Financial institutions are looking to build smarter, more efficient ways to operate, uncovering new opportunities through data. Our clients rely on us as trusted advisors to ingest, interpret, and manage their data. We specialize in Data Products Management, Data Architecture and Engineering, Data Governance and Controls, and Data Analytics and Insights.

We provide constant room for growth through client engagements and personal development. Practitioners develop and lead innovative data techniques and methods, supporting both business and technology leaders. This role offers a unique opportunity to build a professional network, tackle complex data issues, and drive cutting‑edge approaches across industry‑leading clients and domains.

You will be part of diverse teams of professionals across geographies to deliver a wide range of data and analytics services. You will solve complex issues and drive growth across financial services.

• Fostering an innovative and inclusive team‑oriented work environment
• Working in diverse teams of professionals with different backgrounds
• Demonstrating in‑depth technical capabilities and professional knowledge
• Contributing to thought leadership through white papers, point of views, and proof of concepts
• Working in an entrepreneurial environment to pave your own career path
• Ability to meet deadlines, own deliverables and contribute to project delivery

• Undergraduate or Master’s degree in a quantitative field (engineering, computer science, business, economics, finance, statistics, analytics).
• 2–5 years of related experience in banking, capital markets, insurance, or asset management.
• Strong communication (verbal and written) to advocate technical solutions to technical and business audiences.
• Experience working independently, efficiently, and effectively under extreme time constraints and delivering results by critical deadlines.
• Strong analytical and problem‑solving skills.
• Experience with client‑facing activities such as requirements gathering, facilitation, presentation creation, and preparing client‑ready deliverables.
• Proven track record of consistently meeting deadlines and providing reporting and business recommendations in a dynamic environment.
• Good leadership and teaming skills.
• Strong organizational and time‑management skills.
• Ability to integrate new knowledge and adapt to change with a natural curiosity and desire to learn.
• Willingness and ability to travel to meet client needs; travel is estimated at 60%.
• Valid passport.

• Understand business challenges and address remediations through data architecture and engineering solutions.
• Assist clients with development of strategic Data Architecture and Engineering, Cloud Data Modernization, Data migration, and Event‑driven architecture, preferably focused on financial services.
• Develop large data platforms, data warehouses, and data lakes, streaming applications, data ingestion, integration, and distribution pipelines.
• Use latest technologies for data ingestion, integration, transformation, storage, mining/warehousing, big data analytics, and visualization.
• Understand traditional data architecture practices (data warehousing, datahub, MDM, ODS) and transition to Next‑Gen platform architectures such as distributed data lake and Data mesh on cloud.
• Practical…