Data Architecture & Engineering - Manager - Financial Services - Consulting - NYC

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 build a better working world.

EY is the only professional services firm with a dedicated financial services marketplace unit (FSO). Our FSO teams have been at the forefront of every event that reshaped the financial services industry. If you have a passion for rallying to solve the most complex challenges in the industry, 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, uncovering new opportunities through their data. Our clients rely on us as trusted advisors to provide insights on how to ingest, interpret, and manage their data. We specialize in Data Products Management (DPM), Data Architecture and Engineering (DAE), Data Governance and Controls (DGC), and Analytics and Insights.

• Work with diverse teams of professionals across different geographies to deliver a wide range of data and analytics services.
• Solve complex issues and drive growth across financial services.

• Fostering an innovative and inclusive team‑oriented work environment.
• Leading and coaching diverse teams with different backgrounds.
• Providing subject matter expertise in defining technical and business approaches.
• Building strong relationships with clients and cultivating business opportunities.
• Initiating and building thought leadership through white papers, points of view, and proof of concepts.
• Working in an entrepreneurial environment to pave your own career path.

• Undergraduate or master’s degree in a quantitative field (engineering, computer science, business, economics, finance, statistics, analytics).
• About 6+ years of related work experience in banking, capital markets, insurance, or asset management.
• Good verbal and written communication, able to advocate technical solutions and results to technology and business audiences at all levels.
• 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, facilitating meetings, presentation creation, and preparing client‑ready deliverables.
• Prior experience in project management and client serving roles.
• Excellent leadership and teaming skills.
• Strong organizational and time‑management skills.
• Ability to integrate new knowledge, adapt to change with curiosity and desire to learn.
• Willingness and ability to travel ~60% of the time.
• Valid passport.

• Understand business challenges and address remediations through data architecture and engineering solutions.
• Practical experience assisting clients with strategic Data Architecture and Engineering, Cloud Data Modernization, Big Data initiatives, and event‑driven architecture, preferably focused in financial services.
• Experience architecting and designing large data platforms, data warehouses, streaming applications, and data ingestion, integration, and distribution pipelines.
• Practical experience with the latest technologies for data ingestion, integration, transformation, storage, mining/warehousing, big data analytics, and manipulation.
• Deep understanding of traditional data architecture practices (MDM, ODS, data warehousing) and transition to next‑gen platforms such as Hadoop, cloud, distributed ledgers.
• Practitioner experience in multiple data technologies such as:
• Cloud Data Platforms (AWS, Azure, GCP, Databricks, Snowflake)
• Big Data applications and distributed processing (Hadoop ecosystem components)
• Traditional RDBMS (MS SQL Server, Oracle, MySQL, PostgreSQL)
• MPP (AWS Redshift, Teradata, Netezza)
• No
  
  SQL (MongoDB, DynamoDB, Cassandra, Neo4J, Titan, Elasticsearch)
• Streaming platforms and applications (Spark Streaming, Kafka, Storm, etc.)
• Dev Ops (Git Hub, Kubernetes, Jenkins, Terraform)
• Data Modeling…