Data Visualization

Role Overview: You will be responsible for the end-to-end development and delivery of MIS reports and dashboards supporting credit card and lending portfolio acquisition, early engagement, existing customer management, rewards, retention, and attrition. You will partner with business stakeholders to understand requirements and deliver actionable insights through automated reporting solutions. Additionally, you will maintain and optimize existing SAS-based reporting processes while leading the migration to Python/PySpark on Big Data platforms. Your role will involve designing and building interactive dashboards in Tableau for senior leadership and regulatory reporting. You will also build and implement an automated audit framework to ensure data accuracy, completeness, and consistency across the entire reporting life cycle. Collaboration with Data Engineering and IT teams to leverage data lakes and enterprise data platforms is essential. You will be expected to mentor junior analysts and contribute to knowledge sharing across teams, as well as support ad-hoc analysis and audits with quick turnaround and attention to data integrity. Key Responsibilities: - Develop and deliver MIS reports and dashboards for credit card and lending portfolio management. - Partner with business stakeholders to understand requirements and provide actionable insights. - Maintain and optimize SAS-based reporting processes and migrate to Python/PySpark on Big Data platforms. - Design and build interactive dashboards in Tableau for senior leadership and regulatory reporting. - Implement an automated audit framework for data accuracy, completeness, and consistency. - Collaborate with Data Engineering and IT teams to leverage data lakes and enterprise data platforms. - Mentor junior analysts, contribute to knowledge sharing, and support ad-hoc analysis and audits. Qualifications: - Experience in MIS reporting, data analytics, or BI in the Banking/Financial Services, with a strong focus on Credit Cards. - Proficiency in SAS for data extraction, manipulation, and automation. - Advanced skills in Python and PySpark, particularly in big data environments (e.g., Hadoop, Hive, Databricks). - Expertise in Tableau for dashboard design and data storytelling.,