S&P Global Data Analyst Job Alerts 2026 – Apply Soon!

Qualifications

Experience 

• 0–1 year of experience in Fund Administration, Private Equity Operations, or Financial Data Processing.
• Strong analytical mindset with attention to detail and problem-solving ability.
• Certification and experience in MS Office (Excel, Word, PowerPoint); basic knowledge of SQL, Python; familiarity with BI tools is an advantage.
• Exposure to automation, Lean methodologies, or GenAI tools is a plus.
• Good understanding of basic accounting principles (GAAP).
• Excellent written and verbal communication skills in English.
• Ability to work effectively in a team environment under stringent deadline.
• Willingness to work global shifts and extended hours during peak reporting periods.
• Proactive attitude with a willingness to learn, ask questions, and continuously improve.

Domain Knowledge & Skills 

• Basic understanding of Private Equity / Real Estate / Alternative Investment operations, including fund accounting and investor reporting concepts preferred.
• General awareness of capital markets, alternative investments & Private Equity is preferred.

Responsibilities:

• Process and analyze financial documents received from General/Limited Partners, including capital calls, distributions, financial statements, and schedules of investments.
• Access GP portals and repositories to download, categorize, and tag fund-related documents with accurate metadata.
• Extract, standardize, and validate data from Private Equity documents such as Partners’ Capital Account statements, cash flow statements, and investment schedules.
• Identify appropriate accounting breakouts and classify data items related to fund-level investments and portfolio companies.
• Perform data quality checks, resolve exceptions raised through manual QC reviews and automated validation logs, and ensure adherence to defined data standards.
• Conduct routine reporting and basic trend analysis to support internal analytics and operational insights.
• Support data cleansing initiatives to improve accuracy and consistency across datasets.
• Assist with process improvement, Lean initiatives, and automation efforts, including basic SQL-driven data tasks.
• Maintain clear documentation of data collection and validation processes for auditability and future reference.
• Collaborate with team members to deliver individual and team targets with a strong focus on quality, accuracy, and timeliness.
• Participate in ad-hoc projects aligned to business expansion, data enhancement, or automation initiatives.