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(3 - 4 Years) "S&P Global" Hiring: Data Associate On Sept 2022 @ Hyderabad



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Company:       S&P Global

Website:          www.spglobal.com

Eligibility:      Bachelors Degree

Experience:    3 - 4 yrs

Location:        Hyderabad

Job Role:       Data Associate

JOB SUMMARY:

Company Profile:

S&P Global Market Intelligence, formerly S&P Capital IQ and SNL Financial, is a division of McGraw Hill Financial (NYSE:MHFI). The firm is a leading provider of financial and industry data, research, news and analytics to investment professionals, government agencies, corporations, and universities worldwide.

Job Description:
1. Engages with stakeholders to define requirements and usage needs for the measurement of data quality for a specific region or part of a business.

2. Undertakes ownership for the on-going delivery of data quality measurement activities with a concentrated focus on a specific region or part of a business.

3. On identification of data quality issues, performs analysis and escalates for next level review to remediate the issue and achieve high quality data.

4. Performs testing of defined use cases on new technology and deliver results on data tasks performed; identifies sources or errors.

5. Performs basic root cause analysis on smaller self-contained data analysis tasks that may be related to assigned projects or other unfamiliar projects.

6. Delivers testing of defined use cases as part of data audits on new data vendors.

7. Delivers data quality processes to assure S&P Ratings compliance against regulatory requirements.

8. Performs data queries to identify and drive correction of data inconsistencies.

Candidate Profile:
Qualification:
Bachelors Degree or equivalent experience required.

Experience: 3 - 4 years of experience in a data operations role - experience in a data quality role would be an advantage

Required Skills:
1. Proficient technical skills (including Excel, SQL, data extraction tools)

2. General understanding of Financial and Market data

3. General understanding of data and data flows

 













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