Oversee source data processes within enterprise tools, ensuring data quality and consistency. - Monitor system-generated exceptions and variations in source data and key data fields, applying business standards and governed corrections. - Create and monitor internal data quality audits (AWS Quick-sight, Tableau, Power BI), document findings, and review corrective actions with business owners. - Interact with various stakeholders to resolve questions, troubleshoot issues, and validate fixes. - Use SQL to review data and run queries for validation, research, and troubleshooting purposes. - Create, review and interpret Python scripts used in enterprise to support troubleshooting and code reviews; make updates as needed. - Monitor services deployed on Cloud, ideate for new solution and make updates as needed. What Were Looking For:
Bachelors degree in a related field or equivalent combination of education and experience. - Minimum 3 years of relevant experience in data quality, analytics, or related disciplines. - Ability to work independently and collaboratively across teams and domains. - Strong analytical, problem-solving, and communication skills. - Proficiency with Microsoft Office (Excel, Word, Access). - Good knowledge of SQL: Ability to read, understand, and create database queries for data validation and troubleshooting. - Working knowledge of Python: Comfortable Creating, interpreting and reviewing Python scripts to support data processes. - Experience with data visualization tools (such as Tableau, Power BI, and AWS Quick-Sight). - Experience with Cloud services (AWS) is a plus. For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries
Global Hiring and Opportunity at S&P Global:
At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. About the Role:
This Remote role will require you to work only in USA EST hours/India night shift (6PM-3AM IST). S&P Global has recently announced the intent to separate our Mobility Segment into a standalone public company. The Team: The Data Quality team is responsible for ensuring data quality and consistency in source and parsed data for better and trusted deliverables. The Impact: The Data Quality team plays a crucial role in delivering accurate, consistent and reliable data to the clients. As a part of the Data Quality Team, you will work on Global Automotive space to ensure and provide relevant and insightful details regarding various automotive entities. Responsibilities:
Oversee source data processes within enterprise tools, ensuring data quality and consistency. - Monitor system-generated exceptions and variations in source data and key data fields, applying business standards and governed corrections. - Create and monitor internal data quality audits (AWS Quick-sight, Tableau, Power BI), document findings, and review corrective actions with business owners. - Interact with various stakeholders to resolve questions, troubleshoot issues, and validate fixes. - Use SQL to review data and run queries for validation, research, and troubleshooting purposes. - Create, review and interpret Python scripts used in enterprise to support troubleshooting and code reviews; make updates as needed. - Monitor services deployed on Cloud, ideate for new solution and make updates as needed. What Were Looking For:
Bachelors degree in a related field or equivalent combination of education and experience. - Minimum 3 years of relevant experience in data quality, analytics, or related disciplines. - Ability to work independently and collaboratively across teams and domains. - Strong analytical, problem-solving, and communication skills. - Proficiency with Microsoft Office (Excel, Word, Access). - Good knowledge of SQL: Ability to read, understand, and create database queries for data validation and troubleshooting. - Working knowledge of Python: Comfortable Creating, interpreting and
