Wholesale Banking Sr. Data Architect

BankUnited Financial-posted 2 months ago
Miami Lakes, FL
1,001-5,000 employees
Credit Intermediation and Related Activities
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The Wholesale Banking Sr. Data Architect will be responsible for designing, developing, and maintaining the data architecture for the Wholesale Banking Division, ensuring scalable, secure, and efficient data systems to support business intelligence, reporting, and analytics. This role will focus on creating data models, optimizing data pipelines, and ensuring compliance with banking regulations, enabling data-driven decision-making to enhance client services, operational efficiency, and profitability. The Wholesale Banking Division is unique in that no two deals are the same, requiring the candidate to be flexible and adaptable to meet varying requests. This is a hands-on role which requires in-depth knowledge of the financial services sector, emerging trends in the banking industry and experience of collaborating with sales and operational teams.

  • Designs and implements scalable, secure, and high-performance data architectures to support the Wholesale Banking Division's business intelligence, reporting, and analytics needs.
  • Develops and maintain conceptual, logical, and physical data models for structured and unstructured data.
  • Creates and optimizes data pipelines for efficient data ingestion, transformation, and storage.
  • Ensures uniformity with external data sets and maintain consistently (e.g., Client Loan Tapes, Payment Schedules).
  • Integrates data from core banking systems, CRM platforms (e.g., Salesforce), and external sources into a cohesive data ecosystem.
  • Designs and implements ETL (Extract, Transform, Load) processes to ensure seamless data flow across systems.
  • Collaborates with IT teams to ensure data architecture aligns with enterprise systems and cloud-based platforms (e.g., AWS).
  • Establishes and enforces data governance policies to ensure data quality, security and compliance with banking regulations (e.g., Dodd-Frank).
  • Implements data security measures, including encryption and access controls, to protect sensitive financial data.
  • Works with compliance teams to ensure adherence to data privacy and regulatory standards.
  • Optimizes data storage, retrieval, and processing to support real-time and batch analytics.
  • Monitors and tunes database performance, ensuring scalability and reliability for high-volume transactional data.
  • Implements data partitioning, indexing, and archiving strategies to enhance system efficiency.
  • Partners with BI & Reporting teams and analyst, relationship managers, product teams and the Wholesale Banking Chief of Office (COS) to understand data requirements and deliver tailored solutions.
  • Provides technical guidance to data engineers, analysts, and developers on best practices for data management and architecture for Wholesale Banking data.
  • Communicates complex technical concepts to non-technical stakeholders to support strategic decision-making.
  • Evaluates and recommends emerging data technologies, tools, and platforms to enhance the division's data capabilities.
  • Explores opportunities to incorporate AI, machine learning, and big data technologies into the data architecture.
  • Stays updated on industry trends and best practices to ensure the data architecture remains cutting edge.
  • Identifies opportunities and champions best-in-class business transformation and innovation.
  • Works closely with internal/external leads and partners to ensure execution quality and success.
  • Continually acquires and enhances knowledge of both the Bank's and the Operational Division's business strategies and policies, risk management practices and methodologies, product offerings, financial markets, financial instruments, regulatory requirements, back-office processes, and rapidly changing technology to be able to provide effective business solutions, services and support to the end user business lines.
  • Works with technology partners on architecture reviews and ensures solutions are aligned (build-once, multiple re-use) and escalates on any misalignment.
  • Maintains an understanding of financial services markets, the competitive landscape and client/user needs and requirements.
  • Assists with quality assurance testing prior to any release and works with users to facilitate UAT, if needed.
  • Adheres to and complies with applicable, federal and state laws, regulations and guidance, including those related to anti-money laundering (i.e. Bank Secrecy Act, US PATRIOT Act, etc.).
  • Adheres to Bank policies and procedures and completes required training.
  • Identifies and reports suspicious activity.
  • Bachelor's Degree in Computer Science, Data Science, Information Systems, or a related field required.
  • 8+ years of experience in data architecture, data engineering, or related roles, with at least 5 years in the banking or financial services industry.
  • Experience with Wholesale or Corporate Banking data environments is a plus.
  • Experience in data visualization tools (eg, Tableau, Power BI, QuickSight).
  • Experience with machine learning frameworks.
  • Experience with cloud-based data platforms (eg, AWS, EC2, Lambda, Athena, Glue) preferred.
  • 5+ years direct relevant working experience in the financial sector preferred.
  • 8+ years of experience in data analysis preferred.
  • Advanced MS-Excel skills utilizing vlookups and data analysis experience preferred.
  • 4+ years direct experience within an agile framework and Jira experience preferred.
  • Strong knowledge of Python, or R for statistical analysis and modeling.
  • Expertise in database management systems (Oracle, SQL Server, PostgreSQL) and cloud-based data platforms (e.g., AWS).
  • Strong proficiency in SQL for querying and manipulating large datasets.
  • Familiarity with MS Excel (advanced functions, pivot tables, VBA).
  • Knowledge of data warehousing concepts, ETL processes (e.g., Informatica Cloud) and data integration frameworks.
  • Understanding of CRM systems (e.g., Salesforce) and core banking platforms.
  • Strong analytical and problem-solving skills with attention to detail.
  • Excellent communication skills to present complex data insights to non-technical stakeholders and work with cross-functional teams.
  • Understanding of Wholesale Banking products and regulatory requirements is highly desirable.
  • Basic understanding of banking regulations and compliance requirements related to data and reporting.
  • Familiarity with CRM Systems (e.g., Salesforce) and banking software (e.g., Axiom, Precision Lender, Fiserv) preferred.
  • Demonstrated ability to translate complex, technical concepts so that they are clearly understood in support of sound decisions to meet business objectives, preferred.
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