Associate - Index Fulfillment
Core
Associate-level investment data specialist supporting client data implementation projects, onboarding, and analytics enablement within Aladdin.
Role type
Associate investment data implementation specialist
Builds
Client data onboarding workflows and analytics deliverables for Aladdin
Domain
Financial services / Investment data management
Deliverable
production ML models | product features | dashboards & analysis
Required skills
Investment data familiarity, Data mapping, Data normalization, Data validation, Reconciliation, Requirements gathering, Project planning, SQL, Client collaboration, Documentation
Preferred skills
Private markets knowledge, Derivatives knowledge, UNIX/Linux, Python, Java
Technologies
Aladdin, SQL, UNIX/Linux, Python, Java
Responsibilities
Support client data implementations by assisting with requirements gathering, scope clarification, and project planning. Execute assigned tasks within the data workstream and track progress against project milestones. Collaborate with client investment, technology, and data teams to support data mapping, normalization, and implementation activities. Learn and apply Aladdin data conventions and target-state data management workflows. Use standard interfaces and configurable tools to onboard client data from clients and/or third-party data providers. Assist with configuring analytics jobs and deliverables by supporting the setup, validation, and troubleshooting of analytics workflows. Perform data validation, reconciliation, and quality checks; help investigate data issues and support resolution. Support business and technical analysis by documenting client requirements and translating them into clear inputs for data stewards, production solutions, and engineering teams. Participate in client UAT activities by executing test cases, validating results, and documenting findings. Prepare and maintain client-facing documentation using standard templates and support the transition of new clients into production support. Contribute to process improvements, standardization efforts, and internal initiatives aimed at improving data onboarding efficiency and quality.