Data Architecture Group Manager, Senior Vice President

The Architecture Group Manager is accountable for management of complex/critical/large professional disciplinary areas. Leads and directs a team of professionals. Requires a comprehensive understanding of multiple areas within a function and how they interact in order to achieve the objectives of the function. Applies in-depth understanding of the business impact of technical contributions. Strong commercial awareness is a necessity. Generally accountable for delivery of a full range of services to one or more businesses/ geographic regions.

Excellent communication skills required in order to negotiate internally, often at a senior level. Some external communication may be necessary. Accountable for the end results of an area. Exercises control over resources, policy formulation and planning. Primarily affects a sub‑function. Involved in short- to medium‑term planning of actions and resources for own area. Full management responsibility of a team or multiple teams, including management of people, budget and planning, to include performance evaluation, compensation, hiring, disciplinary actions and terminations and budget approval.

• Strategic Leadership:
  Stay abreast of emerging trends in enterprise data architecture and data engineering. Identify opportunities to leverage these technologies to address business challenges within the banking industry. Contribute to the development and execution of Citigroup’s overall data strategy.
• Data Architecture and Engineering:
  Design and implement state‑of‑the‑art data flows, including cloud migration strategies, big data deployment plans, integrations, and supporting infrastructure. Analyze and optimize data storage, governance, and organizational needs across various business units. Develop and maintain a robust and scalable data architecture that supports Citigroup’s current and future needs.
• Technical Expertise:
  Strong experience defining and executing cloud‑first data architecture strategies across public and private cloud environments. Hands‑on expertise with modern data platforms (data warehouses, lakes, lakehouse architectures) and familiarity with data fabric or data mesh patterns. Proven experience in API‑driven data architecture and governance, including standards, lifecycle management, security, and reusable data services. Working knowledge of AI‑ and analytics‑ready data architectures, enabling ML, advanced analytics, and real‑time data use cases.
  
  Experience with distributed data processing technologies such as Spark, Presto/Trino, and Hadoop ecosystems.
• Team Management and
  
  Collaboration:
  
  Effectively lead and manage a geographically dispersed team of data architects and engineers. Collaborate with senior management, business stakeholders, and technical teams to gather requirements, present solutions, and drive consensus. Foster a culture of innovation, collaboration, and continuous improvement within the team.
• Communication and Influence:
  Possess exceptional communication and presentation skills, with the ability to articulate complex technical concepts to both technical and non‑technical audiences. Effectively communicate and present design reports to senior management and C‑level executives. Influence decision‑making and drive alignment across different stakeholders through strong diplomacy and negotiation skills.
• Risk Management and Compliance:
  Demonstrate a strong understanding of risk management principles and ensure compliance with relevant laws, regulations, and internal policies. Proactively identify and mitigate potential risks associated with data architecture and management.

• Minimum of 15 years of experience in data architecture, data engineering, or related field.
• Prior experience as Data Engineer, Data Manager, or Data Scientist is highly preferred.
• Strong understanding of data governance policies and procedures.
• Proven ability to manage complex projects and deliver results in fast‑paced environments.

• Strong communication, diplomacy, and stakeholder management skills.
• Excellent visual presentation and articulation skills.
• Deep understanding of data warehousing, data lakes, and data lakehouse…