Senior Consultant - Financial Services - Data & Analytics - Data Management and Strategy

EY•Charlotte, NC

20d•Hybrid

About The Position

EY is the only professional services firm with a dedicated business unit (“FSO”) focused on the financial services marketplace. Our FSO teams have been at the forefront of every event that has reshaped and redefined the financial services industry. If you have a passion for rallying together to solve the most complex challenges in the financial services sector, come join our dynamic FSO team! Data has yet to be utilized to its fullest potential. Financial institutions are looking to build smarter and more efficient ways to operate their business through new opportunities uncovered by their data. Our clients look to us as trusted advisors to provide insights on how to ingest, interpret, and manage their data. We specialize in Data Management and Strategy (DMS), Data Products Management (DPM), Data Architecture and Engineering (DAE), and Data Analytics and Insights (DAI). You will help our clients navigate the complex world of Information Data Governance and Data Quality, leveraging AI and automation to enhance these processes. The Data Governance and Data Quality Analyst will specialize in serving EY clients in the areas of Data Strategy, Data Governance, Data Quality, Data Definition and Usage, and Data Management. We’ll look to you to provide our clients with a unique business perspective on how Data Strategy, Data Governance, Data Quality, Data Definition and Usage, and Data Management can transform and improve their entire organization—starting with key business issues they face. This is a high-growth area with plenty of opportunities to enhance your skillset and build your career.

Requirements

A bachelor's degree and approximately three years of related work experience; or a graduate degree and approximately two years of related work experience.
A minimum of two years’ experience in providing complex consultative services in the following focus areas: information strategy, data architecture, information/data governance, master data management, data quality, data integration, metadata management, privacy and security, records management, data risk and controls.
A strong working knowledge of evolving concepts and practices for modernizing information management, particularly through AI and automation.
Proficiency in advising clients on the full data supply chain from data wrangling to data consumption via analytics, with a focus on embedding governance in engineering processes.
Proven track record of understanding business challenges and translating them into value-add solutions—strong analytical and problem-solving skills.
Engagement leadership experience, including managing junior-level consulting staff, providing regular status updates, monitoring project economics, and managing client relationships.
Strong analytical and problem-solving skills as well as excellent oral and written communication skills.
A willingness to travel to meet client needs; travel is estimated at 80%. A valid driver’s license in the US and a valid passport required; willingness and ability to travel internationally.

Nice To Haves

Degree emphasis in Finance, Accounting, Economics, Business, Computer Science, IT, or Engineering preferred.
Working knowledge of the modernized information management tool landscape (e.g., Talend, Collibra, Oracle DRM, SAP MDM, Informatica, SQL, Alation, Purview).
Working knowledge of cloud providers like Azure, AWS, GCP, and experience working with offerings from Databricks and Snowflake.
Experience with designing, developing, or implementing AI or other automation solutions to enhance data management and governance.

Responsibilities

Build and maintain relationships with client personnel at appropriate levels, consistently delivering quality client services.
Manage risk and ensure key stakeholders are kept informed about progress and expected outcomes.
Stay abreast of current business and industry trends relevant to the client's business, particularly in AI and automation technologies.
Effectively manage and motivate client engagement teams with diverse skills and backgrounds, providing constructive on-the-job feedback and coaching to team members.
Cultivate and manage business development opportunities, developing and maintaining long-term client relationships and networks.
Manage client engagement teams to implement AI solutions that enhance data governance and quality, ensuring that AI itself is governed effectively to mitigate risks.
Collaborate with engineering teams to embed data management and governance practices into the development lifecycle, ensuring data integrity and compliance from the ground up.