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Connor, Clark & Lunn Financial Group

Data Analyst - Investment Data Architecture

Data ManagementConfirmed live in the last 24 hours
Full-timeVancouver, BC, Canada$85k - $120k

About the Job

Requirements

  • A degree in Finance, Commerce, Business Analysis, or a related field is required.
  • Three to five 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.
  • Ability to elicit requirements, run working sessions, and turn ambiguous business needs into clear, documented requirements and acceptance criteria.
  • Strong written and verbal communication skills, including the ability to explain data concepts to business users and business needs to technical teams.
  • Understanding of data quality, data ownership, data governance, and metadata concepts.

Responsibilities

  • Partner with investment and operations stakeholders to understand data needs and translate them into business requirements, data definitions, business rules, and acceptance criteria for the technical team.
  • Support business data owners in defining and preparing trusted, reusable investment datasets through intake, definition, and readiness using agreed standards, and contribute to ongoing stewardship and lifecycle reviews.
  • Develop conceptual and logical investment data models with business owners and technical partners 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 and confirm delivered data meets business expectations.
  • Work with data owners and stewards to 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, ensuring consistency across systems.
  • Document data models, mappings, data flows, and business processes, and contribute business glossary terms, data definitions, and lineage information to support transparency and governance.
  • Contribute to strategic data projects, including requirements, testing, and release validation, in collaboration with operations, engineering, and senior management.
  • Identify opportunities to improve investment data usability, consistency, and operational efficiency.

Desired Qualifications

  • Progress toward a designation such as the CFA or FRM is an asset.
  • Experience with security master, pricing, or an Enterprise Data Management platform is a plus.
  • 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, or experience defining data entities, relationships, and business rules, is an asset.

About the Company

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