Financial Data Manager Jobs in Toronto, ON (NOW HIRING)

About Citco:

The market leader. The premier provider. The best in the business. At Citco, we've been the front-runner in our field since our incorporation in 1948 led to the evolution of the asset servicing sector itself. This pioneering spirit continues to guide us today as we innovate and expand, push beyond the boundaries of our industry, and shape its future. From working exclusively with hedge funds to serving all alternatives, corporations and private clients, our organization has grown immensely across asset classes and geographies. For us, this progress is a pattern that we'll only maintain as we move forward, always prioritizing our performance. So for those who want to play at the top of their game and be at the vanguard of their space, we say: Welcome to Citco.

About the Team & Business Line:

Fund Administration is Citco's core business, and our alternative asset and accounting service is one of the industry's most respected. Our continuous investment in learning and technology solutions means our people are equipped to deliver a seamless client experience.

We are seeking a Market Data Manager to lead the market data function for a global asset servicing business. This role will be responsible for managing the people, processes, platforms, controls, and data capabilities required to deliver accurate, timely, governed, and cost-effective market data across the organization.

The Market Data Manager will lead a team of market data analysts and business power users who support critical market data processes across fund accounting, NAV production, pricing, reporting, operations, analytics and client service. The role requires strong market data product knowledge, data fluency, vendor management discipline, operational control experience, and the ability to improve a global operating model.

The successful candidate will understand how market data is sourced, validated, enriched, controlled, and consumed across financial services operations. They will be expected to drive improvements in data quality, issue management, automation, vendor performance, licensing compliance, documentation, and stakeholder support.
This is a hands-on leadership role suited to someone who can operate across business, technology, data, vendor, and control functions.

Required Qualifications

• 10+ years of experience in market data, financial data operations, data management, fund accounting support, securities operations, asset servicing, asset management operations, or related financial services roles.
• 5+ years of experience managing analysts, data stewards, operations specialists, market data SMEs, data product teams, or business power users.
• Strong understanding of market data products, including pricing, reference data, FX, rates, benchmarks, indices, ratings, corporate actions, securities attributes, and vendor-derived analytics.
• Experience supporting market data processes in an asset servicing, fund administration, asset management, custody, investment operations, or controlled financial services environment.
• Strong understanding of how market data impacts NAV production, fund accounting, financial reporting, valuation, reconciliations, client reporting, and operational controls.
• Demonstrated experience with data quality management, exception handling, issue resolution, root-cause analysis, control documentation, and operational risk management.
• Strong data fluency, including understanding of data lineage, mappings, identifiers, metadata, data quality rules, golden-source logic, survivorship rules, and data flows.
• Experience working with market data vendors, financial data platforms, data feeds, vendor portals, data dictionaries, and vendor support models.
• Comfort working with technology teams on data feeds, APIs, data platforms, workflow tools, data quality tooling, automation initiatives, and controlled data transformation processes.
• Practical understanding of how AI and machine learning tools can be used to improve data operations, including issue triage, anomaly detection, mapping support, data classification, reconciliation support, metadata extraction, and workflow prioritization.
• Ability to evaluate AI-generated outputs critically, including validating results against source data, business rules, control standards, vendor documentation, and downstream operational requirements.
• Experience defining requirements for AI-assisted or rules-based data workflows, including exception categorization, recommended remediation actions, transformation logic suggestions, and data stewardship queues.
• Ability to identify appropriate and inappropriate uses of AI in market data operations, particularly where valuation, NAV, client reporting, regulatory reporting, or audit evidence may be impacted.
• Strong control mindset, including understanding of audit evidence, maker-checker controls, approvals, override governance, model/output validation, data lineage, and change management.
• Experience working with market data vendors and internal stakeholders on licensing, entitlement management, usage controls, redistribution restrictions, and vendor issue escalation.
• Strong stakeholder management skills across business, technology, procurement, vendor, risk, compliance, audit, product, and client-facing teams.
• Strong written and verbal communication skills, with the ability to explain complex data, vendor, technology, and control issues in business terms.
• Ability to operate in a matrixed global organization and drive standardization across regions, platforms, data consumers, and legacy operating practices.

Preferred Qualifications
 

• Experience using AI, machine learning, or advanced analytics tools to support financial data operations, market data quality, exception triage, reconciliation, data mapping, data transformation, metadata management, or data governance.
• Experience with AI-assisted data triage, including clustering recurring issues, identifying probable root causes, prioritizing exceptions by business impact, and recommending resolution paths.
• Experience with AI-supported data mapping, including vendor-to-internal field mapping, identifier matching, data dictionary comparison, schema alignment, taxonomy management, and metadata enrichment.
• Experience with AI-assisted data transformation and normalization, including rule suggestion, pattern recognition, transformation testing, exception detection, and comparison of transformed data against expected business outcomes.
• Experience using AI to support data management activities such as data catalog enrichment, lineage documentation, control evidence review, policy interpretation, knowledge management, and process documentation.
• Familiarity with responsible AI practices in financial services, including human-in-the-loop review, output validation, explainability, data privacy, access control, auditability, model risk awareness, and prevention of uncontrolled automated decision-making.
• Experience with SQL, Python, APIs, data feeds, data warehouses, data lakes, cloud-based data platforms, or analytical notebooks.
• Experience with data quality tools, workflow platforms, data catalogs, BI tools, master data management platforms, rules engines, or low-code automation tools.
• Experience with Bloomberg, LSEG / Refinitiv, ICE Data Services, FactSet, S&P Global, MSCI, Moody's, Fitch, SIX, Morningstar, DTCC, Broadridge, or similar market data providers.
• Experience with vendor licensing, exchange data policies, entitlement management, redistribution rights, derived data restrictions, display versus non-display usage, and vendor audit readiness.
• Experience rationalizing vendor products, consolidating overlapping data sets, improving entitlement controls, or reducing market data costs.
• Experience supporting audit, SOC, regulatory, client due diligence, or operational risk reviews involving market data, pricing, valuation, or data governance.
• Experience with private markets, alternatives, complex securities, derivatives, fixed income, or multi-asset servicing.
• Experience building dashboards or metrics for market data quality, vendor performance, exception management, control effectiveness, automation adoption, and operational service levels.
• Experience managing global teams or distributed operating models across regions, time zones, and business lines.

Our Benefits

Your well-being is of paramount importance to us, and central to our success. We provide a range of benefits, training and education support, and flexible working arrangements to help you achieve success in your career while balancing personal needs. Ask us about specific benefits in your location.

We embrace diversity, prioritizing the hiring of people from diverse backgrounds. Our inclusive culture is a source of pride and strength, fostering innovation and mutual respect.

Citco welcomes and encourages applications from people with disabilities. Accommodations are available upon request for candidates taking part in all aspects of the selection.
 

Responsibilities

• Lead the market data team supporting global asset servicing operations. 
• Manage market data processes supporting fund accounting, NAV production, pricing, reporting, analytics and operational workflows. 
• Oversee sourcing, validation, enrichment, exception management, and distribution of market data. 
• Maintain inventory of market data products, feeds, vendors, users, data flows, and consumption points. 
• Define and manage market data quality rules, tolerances, controls, and issue escalation processes. 
• Partner with fund accounting, operations, product, technology, procurement, risk, compliance, audit, and client-facing teams. 
• Manage vendor relationships, service reviews, issue escalations, product evaluations, and renewals 
• Support licensing compliance, entitlement management, redistribution controls, usage reviews and vendor audit readiness.
• Identify opportunities to rationalize vendor products, reduce duplicated data sources, and improve cost efficiency. 
• Drive automation of manual market data processes  
• Create dashboards and metrics for data quality, vendor performance, operational service levels, and issue resolution. 
• Establish documentation, controls, and evidence required for audit, client due diligence, and operational risk management. 
• Coach and develop market data analysts and power users. 
• Build a scalable global operating model for market data management.