Portfolio Data Operations Analyst
New
India, US business hours (6:30 PM to 3:30 AM IST)Full-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 2+ years
- Required Skills
- SQLData AnalysisSalesforceJiraMicrosoft ExcelConfluenceGoogle Workspace
Requirements
- 2+ years of experience in financial services, investment operations, asset management, or capital markets environments.
- Strong understanding of trade lifecycle, portfolio data, and middle/back-office operations processes.
- High attention to detail with proven ability to execute structured processes accurately under tight deadlines.
- Strong analytical and problem-solving skills with the ability to investigate complex data issues.
- Excellent communication and interpersonal skills to interact with internal teams, clients, and external data partners.
- Ability to multitask, prioritize effectively, and remain composed in a fast-paced operational environment.
- Proficiency with tools such as Excel, Google Workspace, Jira, Confluence, or similar financial systems.
- SQL or Salesforce is a plus.
- Willingness to work US business hours (6:30 PM to 3:30 AM IST) and adapt to flexible schedules.
Responsibilities
- Perform daily validation and verification checks to ensure accuracy, completeness, and timeliness of client portfolio data within defined SLAs.
- Investigate, troubleshoot, and resolve data pipeline issues, trade processing exceptions, and position discrepancies in collaboration with support and engineering teams.
- Handle data-related queries from clients, internal teams, and external data providers in a timely and structured manner.
- Support the processing and reconciliation of portfolio transactions, ensuring data consistency across systems and workflows.
- Maintain operational documentation, workflows, and procedural guides while ensuring accurate tracking of key operational metrics.
- Collaborate with Product and Engineering teams to identify process inefficiencies and contribute to automation and tooling improvements.
- Assist regional teams with operational tasks, workflow support, and cross-functional data initiatives.
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