Key Responsibilities
1. Monitor Client-Facing Data
- Own the day-to-day monitoring of data displayed across trading applications, mutual fund platforms, Super Apps, and Relationship Manager (RM) dashboards.
- Establish daily, periodic, and event-based validation checks to identify stale, missing, or inaccurate data, including NAV, returns, AUM, and corporate actions.
2. Evaluate Data Sources
- Map each key data point to its current source, including in-house systems, RTAs, exchanges, CMOTS, Morningstar, Value Research, and other financial data providers.
- Evaluate data sources based on accuracy, refresh frequency, coverage, cost, and integration complexity, and recommend whether to retain or replace existing sources.
3. Validate Financial Calculations
- Validate return calculations, including absolute returns, CAGR, XIRR, annualised returns, rolling returns, and trailing returns, along with portfolio valuations, gains, and financial ratios displayed to clients.
- Document calculation logic and methodologies to ensure consistent definitions across Product, Technology, and Compliance teams.
4. Develop New Data Points, Views, and Reports
- Collaborate with Product Managers to define data requirements for new features, such as portfolio analysers, portfolio health scores, fund comparisons, and RM insights.
- Translate business requirements into clear data specifications and support the design of meaningful reports and analytics for clients and Relationship Managers.
5. Escalate and Resolve Data Issues
- Identify and report inaccurate data displayed on client-facing applications to the relevant data owners, track issues through resolution, and validate fixes in the production environment.
- Maintain a comprehensive issue log documenting root causes, business impact, corrective actions, and resolution turnaround times.
6. Data Governance and UAT
- Maintain a data dictionary documenting data definitions, sources, ownership, validation rules, and refresh frequencies.
- Support User Acceptance Testing (UAT) for releases involving changes to financial data, calculations, reports, and client-facing application features.
Required Skills and Knowledge
Financial Data Understanding:
Strong understanding of equity, Futures & Options (F&O), and mutual fund data displayed on trading and mutual fund applications, including the ability to identify anomalies and inconsistencies.Return Calculations:
Hands-on experience with XIRR, CAGR, absolute returns, annualised returns, trailing returns, and rolling returns, with the ability to independently reconcile client portfolio returns using Excel.Fund and Market Metrics:
Knowledge of NAV, AUM, expense ratios, Sharpe ratio, standard deviation, beta, alpha, and commonly used company financial ratios.Financial Data Vendors:
Working knowledge of data providers such as CMOTS, Morningstar, ACE Equity, Value Research, and Accord Fintech, along with RTA data from CAMS and KFin Technologies and exchange data from NSE and BSE.Analytical Tools:
Advanced Excel skills are mandatory. Working knowledge of SQL for querying, validating, and comparing datasets is required. Python and BI tools such as Power BI or Tableau would be an added advantage.Stakeholder Management:
Ability to communicate data issues clearly to data owners, vendors, and technology teams using supporting evidence, while ensuring timely resolution.Attention to Detail:
Strong analytical skills and a high sense of ownership, treating incorrect financial information displayed on client-facing platforms as a priority issue.
Qualifications and Experience
Must-Have Requirements
- Graduate degree in Finance, Commerce, Economics, Statistics, Engineering, or a related discipline. An MBA in Finance or progress towards CFA/FRM certification would be preferred.
- 34+ years of relevant experience in data management, MIS, research, or product data within a broking firm, AMC, wealth management platform, fintech company, or financial data provider.
- Direct experience handling, validating, or monitoring client-facing financial data on digital platforms, including mobile applications or web-based systems.
Good-to-Have Requirements
- Experience working with financial data vendors such as CMOTS, Morningstar, ACE Equity, Value Research, or similar providers.
- Exposure to portfolio analytics, portfolio health scores, investment insights, or RM dashboards.
- Familiarity with APIs and data flows from vendor feeds and internal systems to client-facing applications.
- Relevant NISM certifications.
