Sushma Bartaula Sedhain

Over 6 years of experience in the IT industry with a strong focus on Microsoft SQL Server (2025,2022,2017), spanning the full Software Development Life Cycle (SDLC) including requirements analysis, design, development, testing, deployment, and support across Finance, Insurance, and Healthcare domains. Proficient in requirements gathering, translating business objectives into technical solutions, and supporting BI initiatives with deep involvement in data modeling, dimensional design, and metadata management. Extensive experience in logical and physical data modeling, dimensional modeling using Star and Snowflake schemas, and normalization/de-normalization techniques for efficient data architecture design.

Strong expertise in developing scalable ETL workflows using SQL Server Integration Services (SSIS), with experience in designing robust data flow and control flow pipelines, incorporating error handling, logging, checkpoints, parameterization, and custom transformations including reusable components like a Sequence Generator. Successfully migrated and upgraded legacy DTS packages to SSIS 2025,2022,2017, ensuring stability, performance, and maintainability in production environments. Designed and implemented a custom ETL framework using Master-Child architecture for streamlined package orchestration, execution, and metadata-driven logging.

Hands-on experience in data integration and migration from diverse sources such as Microsoft Access, Excel, flat files, and Oracle databases into centralized SQL Server environments. Expertise in SSAS (SQL Server Analysis Services) including the design and deployment of OLAP cubes, calculated measures, dimensions, hierarchies, partitions, and aggregations, leveraging MDX for querying multidimensional data. Involved in cube optimization and storage configuration with proactive caching strategies for performance enhancement and seamless user experience.

Delivered enterprise-grade reporting solutions using SQL Server Reporting Services (SSRS) and developed parameterized, drill-down, drill-through, and ad hoc reports, utilizing complex expressions, custom functions, and data visualizations. Upgraded SSRS reports from legacy to new SQL Server versions, ensuring backward compatibility, performance tuning, and modern UI alignment. Proficient in writing complex T-SQL scripts including stored procedures, user-defined functions, views, triggers, cursors, and Common Table Expressions (CTEs), with a focus on data integrity and reusability.

Experienced in performance tuning of T-SQL queries and stored procedures using SQL Profiler, Execution Plans, and Database Engine Tuning Advisor; optimized query performance through appropriate indexing strategies and execution analysis. Configured and maintained SQL Server Agent Jobs, alerts, notifications, and email subscriptions for automated report distribution and ETL scheduling. Demonstrated ability in managing database backup/recovery strategies, index maintenance, deadlock resolu

Senior Data Analyst - Compliance & Fraud Analytics and Innovation - Citi Bank - Dallas, Texas

(2026-03)

• Develop and maintain an in-depth understanding of complex Fraud Analytics, Wealth Management, and Private Banking business functions, translating business objectives into data-driven analytics, reporting, and process improvement solutions.
• Partner with business stakeholders, fraud teams, wealth advisors, risk and compliance teams, data engineers, and technology teams to gather, analyze, document, and validate business requirements for analytics and process improvement initiatives.
• Gather and document functional and business requirements, business rules, data requirements, reporting requirements, process flows, acceptance criteria, and system dependencies for new and enhanced analytics solutions.
• Conduct current-state and future-state analysis of complex business processes, identifying process gaps, operational inefficiencies, control weaknesses, and opportunities to simplify and standardize workflows.
• Facilitate requirement-gathering sessions and stakeholder discussions to establish a common understanding of business needs, priorities, dependencies, and expected outcomes.
• Support the planning, research, analysis, development, testing, and implementation of new and enhanced applications, automated workflows, reporting solutions, and data processes supporting Fraud Analytics and Wealth Management operations.
• Analyze large and complex datasets using SQL, Python, Spark, Trino, Hive, Dataiku, and Tableau to identify fraud patterns, anomalies, emerging risk trends, business opportunities, and operational performance drivers.
• Build automated data analysis workflows and scheduled jobs using Python and SQL to streamline recurring risk, fraud monitoring, and business reporting processes.
• Develop automated ETL workflows using Python, SQL, Spark, and Dataiku for Wealth Management reporting, integrating data from portfolio management systems, transaction platforms, market data sources, and other enterprise systems.
• Use Trino and Spark SQL to query and analyze multi-source distributed datasets, improving data accessibility and query performance for business analytics and reporting requirements.
• Perform advanced data extraction, transformation, validation, and reconciliation across Hadoop, Hive, AWS S3, Trino, Spark, and relational databases to ensure accuracy and consistency of business-critical reporting.
• Analyze Assets Under Management (AUM), client transaction activity, revenue metrics, portfolio performance, asset allocation, investment trends, and portfolio risk exposure to support Wealth Management and Private Banking business decisions.
• Conduct client segmentation and investment behavior analysis to identify opportunities for portfolio optimization, improved customer engagement, business growth, and enhanced financial outcomes.
• Develop executive dashboards, KPI reports, and management information using Tableau and Excel to monitor portfolio performance, client growth, investment returns, business profitability, operational metrics, and risk indicators.
• Review and analyze management and regulatory reports, validating business logic, data accuracy, reporting controls, and key metrics while identifying discrepancies and coordinating remediation with appropriate stakeholders.
• Develop ad-hoc reports and analytical work products using SQL, Python, Tableau, Excel, and Spark to support management requests, operational planning, forecasting, regulatory requirements, and business initiatives.
• Automate Excel-based reporting and manual data processes using Python, significantly reducing recurring manual effort while improving reporting consistency, scalability, and data quality.
• Analyze business processes, operational data, and performance trends to identify root causes of reporting, operational, fraud, and data-quality issues and develop recommendations for corrective and preventive actions.
• Collaborate with business and technology teams to evaluate alternative solutions, document findings, assess impacts, and recommend improvements to existing applications, processes, reporting capabilities, and data workflows.
• Support User Acceptance Testing (UAT) by validating requirements against developed solutions, preparing test scenarios and expected results, analyzing defects, and coordinating issue resolution with business and technical teams.
• Assist with documenting new and revised departmental procedures, business rules, process flows, standard operating procedures, data requirements, and reporting controls to improve operational consistency and knowledge sharing.
• Maintain broad knowledge of business processes, applications, data flows, system enhancements, and business strategies, assessing downstream impacts and communicating relevant changes to stakeholders.
• Support risk management, compliance, audit, and regulatory activities by identifying data, process, operational, and reporting risks and ensuring appropriate controls are incorporated into business and analytics processes.
• Apply AI-assisted analytics capabilities in Dataiku to support data exploration, anomaly identification, data-quality analysis, and development of repeatable analytical workflows.
• Utilize Microsoft Copilot to accelerate the creation and refinement of Tableau/Excel reports