S&P Global Hiring - Apprentice – Data Quality

   About the company

S&P Global Inc. is an American publicly traded corporation headquartered in Manhattan, New York City. Its primary areas of business are financial information and analytics.

Job Profile: Apprentice – Data Quality

Qualifications: Bachelor's degree in CS or related field

Duration: 12 months

Experience: Freshers

Job Location: Bengaluru, Karnataka

About The Role:

S&P Global Commodity Insights is seeking candidates for our 12-months’ Apprenticeship program within our Data Quality Team. This role offers invaluable exposure to data management practices and provides a unique perspective on how data quality is maintained and enhanced throughout the data lifecycle. The Data Quality Apprentice will be responsible for supporting data quality initiatives within the Commodity Insights Technology & Data organization. This role will involve assisting in the monitoring and validation of data, identifying data discrepancies, and ensuring data integrity across various datasets. The Data Quality Apprentice will also contribute to the development and maintenance of data quality documentation, including data quality metrics, reports, and improvement plans. 

About The Team:

As part of the Data Quality Team, which operates under the Data Strategy and Governance Tower, we are responsible for overseeing the quality and integrity of data across various systems within the Commodity Insights organization. This role involves coordinating data quality initiatives, prioritizing data validation tasks, ensuring alignment with data governance standards, and maximizing the value delivered through accurate and reliable data.

Responsibilities:

Assist in daily data quality operations, including managing rules, detecting anomalies, and coordinating issue resolution. 

Collaborate with experts to translate business needs into data quality requirements and support issue resolution. 

Support technical teams in prioritizing and setting up data for quality profiling and monitoring. 

Review profiling results and assist in creating reusable custom data quality rules. 

Capture metrics, identify improvement opportunities, & engage stakeholders through training and knowledge sharing.

What We’re Looking For:

Degree in Data Management, CS, Information Systems, or a related field. 

Basic understanding of data management principles and an interest in data quality practices, including data profiling, rule development, and automation. 

Familiarity with data quality tools like soda.io or similar (Great Expectations, Soda, Informatica IDQ, etc.) is a plus. 

Proficiency in SQL for data handling and basic knowledge of Python/PySpark for data analysis and automation. 

Basic knowledge of Power BI for data visualization and reporting.

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