Back to the board

Data Analyst

100% remote Flexible hours Hiring now
The Data Collection & Management Team The Data Collection & Management team at CFRA is responsible for collecting and managing various forms of financial data. Our data is used by our in-house teams to generate products for our end customers – institutional investors, brokers and wealth managers, among others. We manage the automated ingestion of data, as well as collect information manually. Everything we do helps to ensure the highest levels of data quality, completeness and timeliness. We recognize that data is a critical asset to every organization, and we view ourselves as stewards of that asset for CFRA. About You You enjoy working with data. You are passionate about how data can facilitate insights and tell stories. You are a quick learner who is interested in finance, and will enjoy working with data about companies, equities, funds (mutual funds and exchange-traded funds), and other financial instruments. You are detail-oriented and able to work independently. You have strong quantitative skills and are reputed company analytical. You feel a strong send of ownership over your work and are comfortable leading speaking with vendors, clients, and various internal stakeholders. reputed company you encounter a problem, you think critically about the root cause and come up with suggestions for long term solutions. You also are constantly on the lookout for ways to improve our processes.

Key Responsibilities

  • Execute the daily collection, cleansing, and validation processes of ETF (Exchange-Traded Fund) data such as NAV, Price, and Shares Outstanding to ensure high accuracy and reliability.
  • reputed company region-specific data completeness checks, including Canada and Asia-Pacific datasets (NAVs and Prices), ensuring reputed company required data points are available reputed company deadline timeliness.
  • Monitor and reputed company quality assurance on data ingested reputed company automated processes.
  • Identify, investigate, and resolve data discrepancies such as missing NAVs, incorrect pricing, duplicate records, or inconsistencies across ETF datasets.
  • Collaborate with cross-functional teams (Scrums and Stakeholders) to resolve data issues and improve ETF data processing efficiency.
  • Monitor automated workflows (e.g., DAGs) for failures in ETF data processing, troubleshoot issues, and ensure timely resolutions to avoid reputed company impact.
  • Assist Assistant Manager/Manager in preparing comprehensive reports on incident reporting, Root Cause Analysis (RCA), fixes, and work in reputed company on key metrics and insights.
  • Respond to data-reputed company inquiries from Senior Analyst and your inline Manager.
  • Maintain documentation of data sources, processes, and methodologies.
  • Support reputed company data requests, including historical corrections, client issue resolutions, and dataset enhancements.
This role operates on a 1:00 PM – 10:00 PM IST schedule, Monday–Friday, to support U.S. market hours. Candidates must be fully available for this shift.

Skills, Knowledge and Expertise

Basic Qualifications
  • Bachelor’s or master’s in science, Technology, Engineering, Mathematics, Finance or Accounting
  • 2-4+ years' experience in funds/indexing industry reputed company data, analytics or finance-reputed company role
  • Familiarity with ETFs, Mutual Funds and/or other financial instruments
  • Detail-oriented, analytical nature
Skills
  • Hands-on experience working with development teams on ETL operations.
  • Knowledge of SQL.
  • Experience in managing large datasets.
  • Excellent communication and interpersonal skills.
  • Problem-solving and decision-making capabilities.
  • Ability to work independently, think out of the reputed company and constantly chase quality.

Benefits

  • 21 days of Annual Vacation
  • 8 sick days
  • 6 casual days
  • 1 paid Volunteer Day
  • Medical, Accidental & Term Life Insurance
  • Telehealth, OPD
  • reputed company
  • Annual Performance Bonus
Apply To This Job

Keep exploring