Data Business Analyst Lead

This is a fully remote position, open to applicants in Canada.

📋 Description

• Oversee the comprehensive delivery of data-driven investment solutions, starting from requirements gathering and documentation to data analysis, testing, and implementation.

• Facilitate requirements-gathering sessions with investment and business stakeholders.

• Convert business objectives into Business Requirement Documents (BRDs), functional specifications, user stories, and acceptance criteria.

• Create documentation for current and future state business processes, data flows, control points, dependencies, and operational procedures.

• Ensure traceability from business outcomes and requirements through data rules, solution design, testing, defects, implementation evidence, and acceptance.

• Act as a subject matter expert on investment data, encompassing securities, holdings, transactions, performance, benchmarks, and reference data.

• Develop and maintain source-to-target mappings, data dictionaries, business rules, transformation requirements, and data documentation.

• Document end-to-end data lineage and support data governance, controls, and auditability.

• Conduct root-cause analysis for data discrepancies, process interruptions, and control issues.

• Analyze, profile, and reconcile data using SQL and Python.

• Organize data across products, positions, and transactions for reporting and analytics purposes.

• Streamline legacy data sources to align with contemporary data architecture principles.

• Plan and manage User Acceptance Testing (UAT), including test strategy, scenarios, cases, and data, and secure business sign-off.

• Validate data outputs, automate validation tests when feasible, and oversee defect resolution.

• Assist in the design, development, and implementation of data, analytics, and reporting solutions.

• Coordinate release readiness, production deployment, and post-implementation validation.

• Perform pre- and post-implementation analyses and monitor the performance of solutions.

• Design reports, dashboards, and visualizations in Power BI and other visualization tools.

• Create training materials and user guides for self-service analytics.

• Collaborate with investment, operations, risk, compliance, sales, technology, data platform, vendor, and external provider stakeholders.

• Update stakeholders, including senior leadership, on progress, risks, issues, and recommendations.

• Operate independently and manage non-routine situations efficiently.

⛳️ Requirements

• Generally, 7–10 years of relevant experience in business or data analysis, preferably in asset management, investment management, or financial services.

• A post-secondary degree in a related field or an equivalent combination of education and experience.

• In-depth understanding of investment data and asset management operations, including securities, holdings, transactions, performance, and benchmark data across various asset classes.

• Experience in gathering requirements and producing BRDs, functional specifications, user stories, source-to-target data mappings, and lineage documentation.

• Proven track record in planning and executing UAT and data validation, along with supporting solutions through production delivery.

• Advanced SQL proficiency for querying, profiling, reconciling, and validating large and complex datasets.

• Practical knowledge of Python, particularly pandas, for data analysis, automation, and test validation.

• Familiarity with Power BI and other data visualization tools like Tableau and Spotfire for building reports and dashboards.

• Experience with Snowflake and other cloud data lake and data warehouse platforms, such as Azure Data Lake and Databricks.

• Familiarity with SAS or WebFOCUS is a plus.

• Understanding of data governance, data quality, and data lineage practices.

• Experience with Agile delivery methods is beneficial.

• Excellent verbal and written communication skills for bridging business and technical audiences.

• Strong collaboration, influencing, and stakeholder management abilities.

• Robust analytical, problem-solving, and data-driven decision-making skills.

🏝️ Benefits

• Performance-based incentives.

• Discretionary bonuses.

• Additional perks and rewards.

• Health insurance coverage.

• Tuition reimbursement programs.

• Accident and life insurance options.

• Retirement savings plans.

• Comprehensive training and coaching.

• Support from management.

• Opportunities for networking.

• Access to tools and resources to achieve new milestones.

• Accommodations available upon request during the selection process.