T. Rowe Price
Lead Data Analyst - Investment Data Strategy
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The Investment Data Strategy & Architecture team is seeking an experienced Lead Business Analyst to help shape the future of investment data capabilities across the firm. This role sits at the intersection of investment management, data strategy, architecture, and technology delivery.
The successful candidate will partner with Data Engineers, Architects, Front Office Stakeholders (Portfolio Managers, Traders, Research Analysts, Quants), and Technology Leaders to define and deliver strategic data capabilities that enable investment decision-making, analytics, reporting, AI, and operational efficiency.
This role is ideal for someone who combines deep investment domain knowledge with strong analytical, architectural, and technology skills. You will help define enterprise investment data strategy, logical data models, metadata standards, data quality frameworks, and reusable investment data services while driving execution through agile technology teams.
This position is an evolution of the traditional business analyst role, emphasizing strategic thinking, data architecture, and product ownership with a strong technical foundation.
Why Join This Team?
This team is responsible for defining the future state of investment data across the organization. You will have the opportunity to influence strategy, architecture, operating models, governance, and technology investments that support portfolio management, research, trading, analytics, and emerging AI capabilities. The role offers broad exposure across investment functions while providing a unique opportunity to shape foundational capabilities that will be leveraged throughout the firm for years to come.
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This position is best suited for someone who enjoys operating between business strategy, investment domain expertise, data architecture, and technology execution.
Core Responsibilities
- Define and promote the strategic vision for investment data capabilities across the organization.
- Perform deep analysis of investment datasets, workflows, and business processes.
- Identify data quality, lineage, integrity, and operational issues and recommend solutions.
- Support root-cause analysis and remediation efforts across investment platforms.
- Use data-driven insights to influence strategic and architectural decisions.
- Drive adoption of enterprise data architecture principles, standards, and governance frameworks.
- Evaluate current-state data ecosystems and identify opportunities for simplification, standardization, and reuse.
- Support enterprise initiatives related to AI, metadata management, data governance, and data quality.
- Develop process flows, conceptual architectures, capability models, UML diagrams, and solution designs.
- Participate in architecture reviews and provide recommendations on data modeling approaches.
- Translate complex investment processes into scalable technology and data solutions.
Core Competencies
- Strong investment management domain knowledge.
- Strategic thinking and enterprise mindset.
- Strong analytical and quantitative reasoning capabilities.
- Ability to translate business objectives into data and technology solutions.
- Strong stakeholder management and communication skills.
- Systems thinking and architecture-oriented problem solving.
- Ability to balance strategic planning with tactical execution.
- Experience leading cross-functional initiatives across business and technology teams.
- Ability to influence without direct authority.
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Required Qualifications & Experience
- 10+ years of experience in Business Analysis, Data Strategy, Data Architecture, Product Strategy, Investment Technology, or related disciplines.
- Experience within Asset Management, Investment Management, Hedge Funds, Wealth Management, Capital Markets, or related financial services organizations.
- Strong understanding of front-office investment workflows and investment data.
- Experience working directly with Portfolio Managers, Traders, Research Analysts, Risk teams, or Quantitative teams.
- Experience defining business capabilities, operating models, and strategic roadmaps.
- Experience partnering with agile software development teams.
- Demonstrated ability to lead complex cross-functional initiatives from concept through delivery.
- Strong project management and stakeholder management skills.
Preferred Technical Skills
- Advanced SQL skills.
- Python experience for data analysis and prototyping.
- Experience working with data warehouses and analytical platforms.
- Experience creating UML diagrams, process flows, and architecture documentation.
- Strong understanding of relational data modeling concepts.
- Experience with data quality, metadata, lineage, and governance concepts.
- Experience using Jira, Confluence, and related Agile delivery tools.
Work Flexibility:
This position is eligible for hybrid working with up to 3 days per week from home.
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