Director, Investment Data & Intelligence

We are seeking a highly strategic, hands-on Principal / Director of Investment Data Engineering & Visualization to lead the design, development, and evolution of our investment data platform and analytics capabilities. This is a unique opportunity for a leader who thrives at the intersection of investment management, data engineering, analytics, and product innovation.

About the Role

As both a visionary and builder, you will define the firm's investment data strategy while remaining close to execution—architecting platforms, delivering analytics solutions, mentoring engineers, and partnering directly with investment and executive leadership. You will own the end-to-end investment data lifecycle, transforming complex financial and market data into trusted, scalable, and actionable insights that power investment decisions, portfolio management, client reporting, and business growth.

In a fast-paced, entrepreneurial environment, this role requires someone who is equally comfortable designing enterprise architecture, building proof-of-concepts, leading teams, engaging clients, and influencing company strategy.

Responsibilities

Data Strategy & Leadership

• Define and execute the vision, roadmap, and operating model for investment data and analytics.
• Build a scalable foundation for data-driven decision-making across investment, product, operations, and executive teams.
• Establish data governance, quality, lineage, stewardship, and security standards.
• Lead and grow a high-performing team of data engineers, analytics engineers, and visualization professionals.
• Serve as the firm's thought leader for investment data architecture and analytics innovation.

Investment Data Engineering

• Architect and build cloud-native data platforms supporting current and future business growth.
• Develop scalable pipelines and integration frameworks for:
  • Market data
  • Security master and reference data
  • Portfolio holdings and transactions
  • Performance and attribution data
  • Risk analytics
  • ESG and alternative datasets
  • Private market and alternative investment data
• Design data lake, lakehouse, and warehouse architectures that balance flexibility, scalability, and governance.
• Implement robust monitoring, observability, and data quality controls.

Analytics & Visualization

• Create best-in-class investment analytics and visualization platforms.
• Deliver intuitive dashboards and interactive reporting tools for executives, investment teams, clients, and operational stakeholders.
• Develop visualizations supporting:
  • Portfolio performance
  • Asset allocation
  • Risk exposures
  • Attribution analysis
  • Trading activity
  • Capital flows
  • Investor and client reporting
• Enable self-service analytics while maintaining trusted data standards.

Product & Innovation

• Partner with product and investment teams to transform data assets into differentiated products and capabilities.
• Identify opportunities to leverage AI, machine learning, and generative AI to improve investment research, portfolio analytics, and operational efficiency.
• Champion automation and eliminate manual reporting and operational processes wherever possible.
• Explore unconventional approaches and emerging technologies that create competitive advantage.

Business & Stakeholder Partnership

• Work directly with executives, portfolio managers, analysts, and clients.
• Translate business objectives into scalable data and analytics solutions.
• Present findings, recommendations, and platform strategies to senior leadership and external stakeholders.
• Support strategic initiatives, partnership discussions, customer engagements, and growth opportunities.

Qualifications

• Bachelor’s degree in computer science, Engineering, Information Systems, Finance, Mathematics, or related field.
• 10 - 15 years of experience in data engineering, analytics, investment technology, or data platform leadership.
• Experience supporting asset management, wealth management, fintech, hedge funds, institutional investing, private markets, or capital markets.
• Strong understanding of:
  • Portfolio management
  • Investment operations
  • Risk management
  • Performance measurement and attribution
  • Security master and investment reference data
• Expertise in:
  • Python
  • SQL
  • Cloud platforms (Azure, AWS, or GCP)
  • Modern data architecture
  • Data modeling and pipeline development
  • API integration frameworks
• Experience with modern visualization and reporting tools such as Power BI, Tableau, ThoughtSpot, or similar platforms.
• Demonstrated ability to lead while remaining technically hands-on.

Preferred Qualifications

• Master's degree in technical or quantitative discipline.
• CFA, CAIA, CIPM, FRM, or similar industry certifications.
• Experience with:
  • Snowflake
  • Databricks
  • Microsoft Fabric
  • Aladdin
  • Bloomberg
  • FactSet
  • MSCI
  • Morningstar
• Experience building customer-facing analytics products.
• Background in startup, scale-up, or high-growth technology environments.

Leadership Competencies

• Builder mentality with an ownership mindset.
• Balances strategic vision with execution excellence.
• Comfortable operating in ambiguity and rapidly changing environments.
• Strong executive presence and communication skills.
• Ability to influence across technical and business functions.
• Proven track record of building teams, platforms, and processes from the ground up.
• Passionate about innovation and using data to solve complex investment challenges.

Success Measures

In the first 12–18 months, this leader will:

• Build and scale a modern investment data platform capable of supporting significant business growth.
• Establish trusted, governed investment data across the organization.
• Launch executive-grade portfolio, risk, and performance analytics dashboards.
• Increase adoption of self-service analytics and reduce dependency on manual reporting.
• Deliver automation initiatives that improve operational efficiency.
• Create a roadmap for AI-enabled investment intelligence and decision support.
• Recruit and develop a world-class data engineering and analytics team.
• Position data and analytics as a strategic differentiator for the company.

Schedule

• Hybrid Office Environment (Tuesdays, Wednesdays, Thursdays)
• Frequent Travel: 25 to 50%

Pay

• Salary range: $173,000 - $215,000 annually
• Eligible for an Annual Bonus based on the Company Bonus Plan/Individual Performance at the Company’s discretion

Salary may vary above and below the stated amounts based on qualifications, experience, geography, work location designation (in-office, hybrid, remote), and operational needs.