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Senior Financial Data Analyst
SimCorp
Toronto, CAN
Full-time
Mid-Senior
Onsite
$88,960 to $133,440
Discovered 1 weeks ago
Financial instrument dataMarket and master data managementData qualityData governanceOperational risk managementFinancial instruments and markets
Free
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Ready to ScanKey skills for this role
Financial instrument dataMarket and master data managementData quality
Role Overview
The Lead Financial Data Analyst executes collection, composition, control, and distribution of market and master data for financial instruments for SimCorp clients under service-level agreements.
The role answers client questions, analyzes financial instrument data to resolve incidents, and follows operational risk, data governance, and quality frameworks.
The position requires substantial knowledge of financial instruments and a client-focused mindset, including coaching other team members.
Key Skills for This Role
Financial instrument dataMarket and master data managementData qualityData governanceOperational risk managementFinancial instruments and markets
Full Job Posting
Why This Role Is Important
The Lead Financial Data Analyst executes collection, composition, control, and distribution of market and master data for financial instruments for SimCorp clients under service-level agreements.
The role answers client questions, analyzes financial instrument data to resolve incidents, and follows operational risk, data governance, and quality frameworks.
The position requires substantial knowledge of financial instruments and a client-focused mindset, including coaching other team members.
Responsibilities
- Execute daily service deliverables for collecting, composing, controlling, and distributing financial instrument data.
- Perform quality checks, follow runbooks and governance frameworks, and analyze unexpected data behavior.
- Resolve client data questions, service requests, and audit support needs.
- Comply with operational risk frameworks such as SOX and RACE.
- Improve operational processes, data quality checks, and system functionality.
- Identify client requirements, special data treatment, and other service-scope demands.
- Exchange knowledge across Data Operations teams to maintain consistent service levels.
- Monitor and report issues across the data supply chain and trigger resolution processes.
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