Data Visualization Manager, VP

JPMorganChase•Jersey City, NJ

About The Position

As a Vice President, Data Visualization Manager within Sales Science, you will translate sales, service, and marketing data into business intelligence reporting that supports branch leadership. You will own end-to-end delivery of dashboards—from data preparation and metric definition to visualization design and release readiness. You will partner with analytics, engineering, and business stakeholders to build scalable, self-service reporting that drives action. You will balance speed and rigor, ensuring outputs are accurate, explainable, and easy to use. You will raise the bar on storytelling, user experience, and operational excellence across the reporting portfolio. This team supports leaders across Community Banking and Wealth Management by measuring program performance and identifying opportunities to improve banker and advisor outcomes. Your work will focus on branch-facing programs and frontline performance drivers, with reporting used by audiences ranging from analysts to senior executives. You will help standardize key performance indicators, reduce manual reporting effort, and improve how insights are communicated. As AI capabilities evolve, you will identify practical use cases (for example, faster analysis drafting and clearer dashboard narratives) and implement them with appropriate validation and governance. Success means trusted metrics, fast cycle times, and dashboards that consistently lead to decisions.

Requirements

6 years of experience delivering analytics, reporting, or data management work in sales, marketing, customer analytics, CRM, or financial services
4 years of experience building advanced Tableau dashboards (including calculated fields, parameters, and performance optimization)
3 years of experience writing and optimizing SQL for large datasets and recurring reporting use cases
Experience preparing and transforming data using an ETL or wrangling tool (for example, Alteryx, Python, or R)
Experience designing dashboards with strong user experience principles (clear hierarchy, intuitive navigation, and actionable callouts)
Experience partnering with cross-functional teams (analytics, engineering, product, and business stakeholders) to deliver reporting solutions
Demonstrated ability to translate business questions into measurable metrics and structured analyses
Strong written and verbal communication skills, including experience presenting insights to senior stakeholders
Experience managing multiple deliverables with timelines, dependencies, and milestone-based execution

Nice To Haves

Experience using Salesforce data for analytics and reporting (including blending with other enterprise data sources)
Tableau certification and/or a portfolio demonstrating dashboard design and storytelling ability
Experience with modern MPP databases and large-scale data concepts (for example, Teradata, Greenplum, Snowflake, Databricks or Hadoop ecosystems)
Experience building or leveraging a semantic layer, metric store, or enterprise metric dictionary
Experience applying responsible AI or generative AI tools to analytics workflows with documented validation and controls
Experience with statistical or machine learning techniques for exploratory analysis or performance driver identification

Responsibilities

Own end-to-end development of business intelligence dashboards, including data preparation, testing, publishing, and ongoing enhancements using Tableau, SQL, and Alteryx
Define and document key performance indicators, business rules, and metric logic to ensure consistent interpretation across stakeholders
Build executive-ready, user-friendly dashboards that prioritize clarity, performance, accessibility, and actionability
Deliver ad-hoc analyses with strong synthesis, converting ambiguous questions into structured analyses and recommendations
Partner with data engineering and analytics teams to productionize reusable datasets and self-service data products
Query and integrate customer relationship management data (including Salesforce where applicable) with other sources to create decision-ready datasets
Implement automation for recurring reporting processes, quality checks, refresh monitoring, and alerting to reduce manual effort
Apply responsible AI practices to enhance analytics workflows (for example, AI-assisted drafting of queries or narratives with human review and validation)
Coach and support junior analysts by establishing standards, templates, and review practices to improve quality and throughput
Manage work plans, timelines, and stakeholder communication across a prioritized reporting backlog
Present insights through clear storytelling tailored to audiences ranging from frontline partners to senior executives