Banking Support Analyst 1 - Officer

As a Data/Information Management Senior Analyst at Citi, you will be responsible for ensuring the organization's data is accurate, complete, consistent, and reliable to support strategic planning and operational efficiency. Your role will involve profiling data, authoring data quality rules, monitoring data pipelines, managing metadata, and remediating data concerns. You will also be tasked with designing, developing, and deploying scalable AI-powered solutions to enhance enterprise workflows and decision-making. Key Responsibilities: - Maintain Data Catalog/Dictionary by documenting and maintaining business, technical, and operational metadata, including data lineage, definitions, and data standards. - Utilize metadata for Data Lineage Mapping to understand how data flows from source systems to downstream reporting and identify potential impact areas. - Ensure Policy Compliance by making sure all data assets adhere to defined data governance policies and data privacy regulations. - Perform Data Profiling by executing deep profiling of large datasets to understand data structure, patterns, and content, identifying anomalies or missing information. - Investigate Root Cause Analysis (RCA) to determine the root cause of data quality issues and distinguish between upstream processing errors and data entry errors. - Collaborate with business stakeholders to define and validate business rules for Rule Definition and implement data quality rules, checks, and controls using SQL, Python, or specialized DQ tools. - Continuously monitor data pipelines, ETL processes, and dashboards for Data Monitoring and Reporting to proactively identify data quality issues and operational anomalies. - Identify, document, and triage data quality issues for Issue Resolution, develop and execute remediation plans, and collaborate with cross-functional teams for Data Concern Remediations. Qualifications Required: - Proficient in Python, SAS, SQL, Teradata, and Collibra with experience in prompt engineering and building LLM-based applications, AI agents, or autonomous workflows. - Good understanding of Banking domain, Audit Framework, Data quality framework, Risk & control Metrics, and Data Acumen. - Ability to explore data, translate it into business context, establish quality standards, identify trends, investigate quality issues, and understand its ultimate utility. - MBA / Masters Degree in Economics / Statistics / Mathematics / Information Technology / Computer Applications / Engineering from a premier institute. BTech / B.E in Information Technology / Information Systems / Computer Applications. - 9-10+ years of hands-on experience in people management, delivering data quality, MIS, data management with at least 2-3 years experience in the Banking Industry. At Citi, you will have the opportunity to work in a dynamic and fast-paced environment, contribute to organizational initiatives, and collaborate with diverse functional areas to drive data-driven transformation across the organization. As a Data/Information Management Senior Analyst at Citi, you will be responsible for ensuring the organization's data is accurate, complete, consistent, and reliable to support strategic planning and operational efficiency. Your role will involve profiling data, authoring data quality rules, monitoring data pipelines, managing metadata, and remediating data concerns. You will also be tasked with designing, developing, and deploying scalable AI-powered solutions to enhance enterprise workflows and decision-making. Key Responsibilities: - Maintain Data Catalog/Dictionary by documenting and maintaining business, technical, and operational metadata, including data lineage, definitions, and data standards. - Utilize metadata for Data Lineage Mapping to understand how data flows from source systems to downstream reporting and identify potential impact areas. - Ensure Policy Compliance by making sure all data assets adhere to defined data governance policies and data privacy regulations. - Perform Data Profiling by executing deep profiling of large datasets to understand data structure, patterns, and content, identifying anomalies or missing information. - Investigate Root Cause Analysis (RCA) to determine the root cause of data quality issues and distinguish between upstream processing errors and data entry errors. - Collaborate with business stakeholders to define and validate business rules for Rule Definition and implement data quality rules, checks, and controls using SQL, Python, or specialized DQ tools. - Continuously monitor data pipelines, ETL processes, and dashboards for Data Monitoring and Reporting to proactively identify data quality issues and operational anomalies. - Identify, document, and triage data quality issues for Issue Resolution, develop and execute remediation plans, and collaborate with cross-functional teams for Data Concern Remediations. Qualifications Required: - Proficient in Python, SAS, SQL, Teradata, and Collibra