Data Analyst, Investment Data Architecture

Role Overview

What You Will Do

• Partner with investment and operations stakeholders to translate data needs into business requirements, data definitions, business rules, and acceptance criteria.
• Support business data owners in defining and preparing trusted, reusable investment datasets through intake, definition and readiness.
• Develop conceptual and logical investment data models and explain them to technical and non-technical stakeholders.
• Collaborate with data engineers and business teams to define and validate business transformation rules and source-to-target mappings.
• Define data quality rules and critical data elements and analyze data-quality exceptions and reconciliation breaks.
• Act as a subject-matter resource on security master, pricing, holdings and reference data across equity, fixed income, and derivatives.
• Document data models, mappings, data flows and business processes and contribute business glossary terms, data definitions and lineage information.
• Contribute to strategic data projects including requirements, testing, and release validation.
• Identify opportunities to improve investment data usability, consistency and operational efficiency.

What You Bring

• Degree in Finance, Commerce, Business Analysis, or a related field; progress toward CFA or FRM is an asset.
• 3-5 years of experience in investment management or financial services, ideally in investment data management, investment operations, or business analysis.
• Hands-on knowledge of equity, fixed income, or derivative data is required; security master, pricing, or EDM platform experience is a plus.
• Proven ability to elicit requirements, run working sessions, and turn ambiguous business needs into documented requirements and acceptance criteria.
• SQL is an asset; familiarity with Python, PySpark, Lakehouse architecture, Microsoft Fabric or similar data platforms is a plus.
• Exposure to conceptual or logical data modeling is an asset.
• Understanding of data quality, data ownership, data governance and metadata concepts.
• Excellent written and verbal communication skills.
• Curious, detail-oriented self-starter who delivers outcomes with measurable results.

Compensation

• Expected base salary range is $85,000-$120,000.
• Actual starting salary may fall below or above the midpoint depending on relevant experience, skills, qualifications, and internal equity.

What We Offer

• Flexible work practices supporting work-life balance and flexibility in where and how employees work.
• Continuous learning budgets, paid study days, and support for professional designations.
• Competitive total compensation, retirement savings support, wellness credits, enhanced parental leave, and comprehensive health benefits.
• Social events, volunteering, and a strong commitment to corporate social responsibility.

Recruitment Notes

• Accommodations are available on request for candidates taking part in all aspects of the recruitment and selection process.
• AI may be used to support certain stages of the screening and recruitment process.