Business Data Analyst

Role overview

This role is an immediate need with a direct client in the Capital Markets space. The position is based in Toronto, Ontario and follows a hybrid schedule of 4 days per week onsite. The main objective is to work closely with Capital Markets business partners, Quantitative & Technology Services (QTS) IT groups, and enterprise teams to help expand the organization’s Data Strategy adoption across Capital Markets.

The analyst will collaborate with application teams moving onto the Data Insights platform, capture and refine feature needs, and translate business and data needs into clear functional direction. The work also includes reviewing datasets, shaping requirements for sourcing, information security classification, and transformations, and coordinating with platform engineering teams so that the intended functionality is delivered correctly.

Additional responsibilities include defining KPIs, reviewing product performance, preparing business requirements, developing functional specifications and design documents aligned to the existing Data Lake architecture, and performing market research to better understand customer needs, market trends, and competing solutions relevant to Capital Markets challenges.

Core responsibilities

• Run requirement-gathering sessions with application teams adopting the Data Insights platform, clarify business objectives, and confirm that the solution matches the intended use case.
• Lead workshops and information sessions, guide discussions, manage group interaction, and document business use cases, feasibility findings, and supporting diagrams.
• Work with platform engineering teams to ensure technical dependencies, integrations, and data requirements are fully understood.
• Validate requirements and analysis models with stakeholders through reviews and walkthroughs.
• Confirm that system specifications align with business expectations and help negotiate practical solutions when needed.
• Examine incoming datasets to define sourcing needs, provisioning requirements, and transformation logic.
• Perform data coverage checks using tools, Python, and SQL Server queries to verify whether sourcing requirements are satisfied for business scenarios.
• Interpret compliance and information security standards and apply them appropriately to datasets and business requirements.
• Use statistical techniques to identify trends, patterns, and insights that support diagnostic and predictive analytics.
• Define data accuracy needs, assess solution alternatives, and outline remediation steps if issues or breaches occur.
• Build productive working relationships with stakeholders while gathering, validating, and approving requirements.
• Take part in deliverable reviews and inspections to help maintain quality.
• Develop a strong end-to-end understanding of the product and deliver demos tailored to the audience.
• Support user acceptance testing, implementation planning, post-release validation, and L2 production incident review.
• Identify opportunities to automate, simplify, and streamline business processes and workflows.
• Work with the product manager to prioritize the backlog and track dependencies.
• Manage risks, assumptions, and constraints tied to requirements, and escalate appropriately when needed.
• Create UAT plans that cover business scenarios, edge cases, and what-if analysis.
• Prepare and execute post-implementation validation plans and partner with business teams to confirm release quality.
• Handle multiple priorities, own assigned work, and maintain clear communication with stakeholders.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, or a related discipline, plus 5 years of professional experience.
• Experience in business analysis and requirements gathering for data ingestion and transformation platforms in the financial industry.
• Ability to conduct market research focused on customer needs and market trends within Capital Markets.
• Experience supporting the full product development lifecycle from planning through deployment.
• Hands-on data analysis experience with trading data such as trades, executions, and orders, including SQL-based anomaly checks, linkage analysis, and transformation rule definition.
• Ability to identify patterns and relationships in SQL, Spark SQL, Jupiter Notebook, and data visualization tools such as Tableau.
• Proficiency in data manipulation, aggregation, and analysis using Python.
• Ability to act as a bridge between Architecture, Development, QA, UI/UX, and client teams.
• Nice to have: experience with cloud-based projects, including Microsoft Azure.
• Prior experience working as a data analyst.

Additional information

This is a contract role. The engagement is for a hybrid work model in Toronto, Ontario, with 4 days per week onsite. An updated resume was requested in the source post, but no external application link is included here.

Company information

Iris Software Inc. is the hiring company named in the source. The contact details and office address were included in the original posting and have been omitted here for privacy and formatting consistency.