Join the Customer Loyalty Analytics Team within Consumer & Community Banking Data & Analytics and help shape how Customer Experience survey data is managed, governed, and activated across the firm. In this role, you will lead the data domain architecture and operating framework that enables scalable survey execution, interactive reporting, and actionable insights across channels, products, and Customer Experience functions. You will partner with stakeholders to modernize processes, improve data quality and controls, and unlock more value from platforms like Qualtrics. If you enjoy building pragmatic data solutions, influencing roadmaps, and enabling teams to make better decisions, this role offers meaningful impact and strong career growth.
**Job summary **
As a Data Domain Architect Lead - VP in the Customer Loyalty Analytics Team within Consumer & Community Banking Data & Analytics, you will define and drive the strategy, operating framework, and technical capabilities for Customer Experience survey data. You will lead efforts to ensure data is fit-for-use, governed as a corporate asset, and delivered through reliable platforms, pipelines, and analytics products (e.g., dashboards, taxonomies, automated execution workflows). You will translate business needs into scalable data designs while ensuring adherence to controls and operational risk requirements. You will help stakeholders efficiently identify themes and insights from structured and unstructured feedback, enabling measurable improvements to the customer journey.
You will be a key connector across product, channel, analytics, and technology partners—balancing strategic roadmap development with hands-on design, testing, and delivery. Your work will focus on maximizing enterprise platform capabilities (including Qualtrics XM), improving automation and operational efficiency, and reducing duplication across data domains. You will also evaluate emerging technologies (including Generative AI tooling where appropriate) to improve how survey data is prepared, interpreted, and delivered to users.
**Job responsibilities **
- Own the operating framework and deployment strategy for Customer Experience survey data, leveraging appropriate platforms and tools.
- Maximize value from the Qualtrics Experience Management platform by enabling adoption of key features and scalable capabilities.
- Deliver Customer Experience reporting solutions (e.g., interactive dashboards) to support internal stakeholder decision-making.
- Lead the development and refinement of Customer Experience taxonomies to enable efficient identification of themes in unstructured feedback (e.g., survey verbatim).
- Lead the design, testing, and deployment of technical solutions that enable survey execution and improve efficiency through automation.
- Drive operational risk reduction and execute activities required to adhere to controls requirements.
- Profile, wrangle, and prepare data from diverse sources; develop transformation logic using Python or SAS and/or tools such as Alteryx.
- Analyze business processes to identify data needs and determine whether available data is fit for use for specific processes and outcomes.
- Lead use case and requirements definition and support design, testing, and implementation of data delivery and analytics capabilities.
- Define and manage data as a corporate asset by establishing metadata, authoritative sources, data quality rules, security requirements, and data flows, aligned to firm principles, standards, and controls.
- Build and maintain strategic roadmaps for the Customer Experience survey data domain, identifying opportunities to improve utility and eliminate duplication across domains and platforms.
**Required qualifications, capabilities, and skills **
- Bachelor’s degree or equivalent experience in a quantitative or related field.
- 5+ years of related professional experience in data, analytics, or Customer Experience technology and reporting.
- 3+ years of experience with the Qualtrics Experience Management (XM) platform.
- 1+ year of experience using Generative AI tools such as LLM Suite.
- Demonstrated ability to define data requirements and translate business needs into scalable technical designs and delivery plans.
- Proven ability to define data governance artifacts including metadata, authoritative sources, data quality rules, security requirements, and data lineage/flows. J
- Experience profiling and transforming data using languages such as Python or SAS and/or tools such as Alteryx.
- Strong stakeholder management skills with experience delivering reporting or analytics products to business users.
- Ability to lead design, testing, and deployment activities while managing operational risk and controls expectations.
Preferred qualifications, capabilities, and skills
- Broad expertise in data technologies such as data warehousing, ETL, data quality concepts, business intelligence, analytics tooling, unstructured data, and machine learning.
- Technical understanding of relational database systems such as Teradata and Oracle.
- Hands-on experience with data modeling techniques and tools.
- Excellent command of SQL.
- Advanced analytical thinking and problem-solving skills.
- Strong interpersonal and communication skills.