SENIOR DATA QUALITY SPECIALIST

The Team:The Data Quality Team is dedicated to ensuring the integrity, accuracy, and reliability of data across all operational processes within S&P Global. Our focus is on implementing robust data quality practices that align with our organizational goals of Accuracy, Timeliness, and Comprehensiveness. We work collaboratively with various departments to identify, analyze, and rectify data quality issues, driving continuous improvement and delivering exceptional outcomes for our clients.

The Impact:In this role, you will be instrumental in maintaining high data quality standards across our datasets. You will conduct thorough data quality assessments, identify discrepancies, and implement corrective actions to ensure our data meets the highest quality benchmarks. Your analytical skills will be essential in providing insights that inform decision-making and enhance overall data quality. If you are passionate about data integrity and have a proactive approach to problem-solving, we invite you to join our team.

Responsibilities:

• Conduct comprehensive data quality assessments to identify anomalies, inconsistencies, and defects within datasets.
• Develop and implement data quality frameworks, policies, and procedures to ensure adherence to quality standards.
• Collaborate with data operations and management teams to address data quality issues and implement solutions.
• Analyze data quality metrics and trends, providing actionable insights to improve data integrity across the organization.
• Design and execute data quality audits and checks, reporting findings and recommending improvements.
• Maintain detailed documentation of data quality processes, assessments, and corrective actions taken.
• Provide training and support to team members on data quality best practices and tools.
• Monitor and report on data quality performance using scorecards and dashboards, ensuring transparency and accountability.
• Foster a culture of continuous improvement by identifying opportunities to enhance data quality processes and practices.
• Serve as a subject matter expert on data quality tools and methodologies, providing guidance to junior team members.
• Familiarity with generative AI tools such as Spark Assist to enhance data quality processes and support decision-making.

What Were Looking For:

• A full-time MBA or postgraduate degree in a relevant field is preferred.
• Minimum 2 years of experience in Data Quality Management or a related field, with a strong understanding of data quality concepts; knowledge of general fundamentals datasets will be considered an added advantage.
• Proficiency in data quality tools and techniques, with experience in SQL and data analysis; candidates with certifications in quality management, such as Green Belt Six Sigma, will have an added advantage.
• Strong analytical skills with the ability to interpret complex data sets and make data-driven decisions.
• Excellent communication and interpersonal skills, with a client-focused approach and the ability to collaborate effectively across teams.
• Familiarity with reporting and visualization tools such as Tableau, Power BI, or similar is a plus.
• Willingness to adapt to changing priorities and work under pressure to meet deadlines.
• A proactive mindset with a commitment to achieving high standards of data quality and integrity.
• A curious and innovative mindset, with a passion for experimenting with emerging technologies, including generative AI and other advanced tools to enhance data quality processes.
• A proactive problem-solver who embraces creative exploration to identify data quality issues efficiently, at scale, and with forward-thinking solutions.
• Compustat Fundamentals FR knowledge is an added advantage