Museb Shaik

Projects:

• Lease Accounting, GL Integration – Awarded ‘Best Integration to 3rd Party Systems’ at the IBM TRIRIGA World Awards 2022.
• Data integrations to FDV (Financial Data Vault).
• Amazon QuickSight dashboard for analytics.

Roles and Responsibilities:

• Led QA efforts for the Lease Accounting module, ensuring compliance and stability in IWMS applications, like TRIRIGA and Tango.
• Designed and implemented test plans and strategies for integrations between IWMS, financial systems, and cloud-based services.
• Managed test automation for integrations, leveraging Python, SQL, and AWS services (SQS, SNS, Lambda, Redshift) to streamline data reconciliation and validation.
• Designed and managed test automation frameworks using Python, Selenium, Tosca, and SQL, improving regression testing efficiency by 40%.
• Implemented and maintained test management and defect tracking in qTest, Jira, and Confluence, streamlining testing workflows and reporting.
• Developed and executed performance and load testing using Neoload and JMeter, ensuring system scalability and optimal database performance for AWS Redshift and SQL-based applications.
• Managed integration testing for APIs leveraging AWS Lambda, SQS, SNS, and Redshift, ensuring seamless data synchronization across TRIRIGA, Tango, and financial systems.
• Oversaw API testing for real-time lease and accounting data synchronization, ensuring seamless workflows across enterprise applications.
• Played a key role in the IWMS upgrade project, driving risk assessments, dependencies analysis, and test validation to ensure a smooth transition.
• Led a global QA team, managing resource allocation, reviews, and test execution across multiple regions and time zones.
• Established CI/CD-driven test automation frameworks, improving efficiency and reducing defects in lease accounting workflows.
• Provided business process advisory on lease financials, ensuring data accuracy and compliance in TRIRIGA and Tango implementations.
• Collaborated with cross-functional teams (Finance, Real Estate, and IT) to enhance integration testing and optimize lease management processes.
• Managed QA governance, stakeholder reporting, and defect triaging, ensuring high-quality releases and system stability.
• Acted as a strategic advisor to Real Estate, Finance, and IT leadership, aligning system capabilities with corporate real estate objectives, lease accounting standards, and financial compliance.
• Led business process transformation initiatives, optimizing lease administration workflows, financial reconciliations, and asset lifecycle management within the system.
• Conducted business impact assessments for system changes, ensuring alignment with Amazon’s operational efficiency goals, and scalability needs.
• Designed and implemented a lease governance framework, enhancing contract lifecycle visibility, and financial forecasting accuracy.
• Facilitated executive-level workshops to drive decision-making on system enhancements, integration strategies, and process automation opportunities.

Projects:

• Integrated Capital Project and Financial Reporting System: Developed a system that integrates capital project progress with financial reporting to give stakeholders a comprehensive view of project status, financial health, and potential risks of projects exceeding budget or timelines.
• Capital Asset Lifecycle Management: Created a system to track capital assets from acquisition to disposal, integrating data from finance, operations, and maintenance departments. The system provided insights on asset depreciation, repair schedules, and total cost of ownership.

Roles and Responsibilities:

• Led QA strategy and automation for Capital Projects and Financial Reporting modules, ensuring data integrity, compliance, and performance optimization.
• Designed and implemented test automation frameworks using Python, Selenium, SQL, PyTest, and QA tools like JMeter, Locust, and Postman, streamlining validation for financial data and capital project tracking.
• Developed and executed integration testing for APIs and cloud services, leveraging AWS Lambda, SQS, SNS, Redshift, and DynamoDB for seamless data flow across Starbucks' financial systems.
• Conducted end-to-end data reconciliation automation using SQL, Python, ETL pipelines, and leveraging Jenkins, Git, Docker, and Kubernetes for test execution efficiency, validating financial reporting accuracy, and detecting discrepancies.
• Managed performance and load testing using JMeter, Locust, and LoadRunner, ensuring system scalability, and optimizing database queries for Redshift and SQL Server.
• Led CI/CD implementation for test automation using Jenkins, Git, Docker, and Kubernetes, enhancing test execution efficiency and deployment reliability.
• Played a key role in TRIRIGA system upgrades, performing risk assessments, database migrations, API versioning validation, and post-implementation monitoring.
• Oversaw UAT, functional, regression, and integration testing, ensuring seamless workflows between Reporting systems, Tableau, SAP, and third-party financial applications.
• Led a global QA team, managing test case development, defect triaging, sprint planning, and cross-functional collaboration with Finance, Real Estate, and IT teams.
• Provided business process advisory, optimizing lease financial workflows, cost tracking, vendor payment processing, and reporting automation within IWMS applications.

Roles and Responsibilities:

• Designed and implemented QA strategy and automation frameworks for lending, treasury, and financial reporting systems, ensuring data integrity, compliance, and performance optimization.
• Collaborated with cross-functional teams to streamline loan origination (nCino, Loan IQ), payments (SWIFT, ACH, RTP), and risk management workflows (AML/KYC, Basel III, Dodd-Frank).
• Led the development and execution of test automation frameworks using Python, Selenium, PyTest, and Robot Framework, optimizing validation for financial data, transaction processing, and regulatory reporting.
• Managed integration testing for APIs and cloud-based financial platforms, leveraging AWS Lambda, SQS, SNS, Redshift, and DynamoDB to ensure seamless data flow across banking and financial systems.
• Conducted end-to-end data reconciliation automation, using SQL, Python, and ETL pipelines to validate financial reporting accuracy and detect discrepancies across SAP FICO, Oracle ERP, and Snowflake.
• Led performance and load testing using JMeter and Locust, ensuring system scalability and optimizing database queries for Redshift, Snowflake, and SQL Server.
• Implemented CI/CD pipelines for test automation using Jenkins, Git, Docker, and Kubernetes, enhancing deployment efficiency and test execution reliability.
• Played a key role in system upgrades, performing risk assessments, database migrations, API versioning validation, and post-implementation monitoring.
• Managed UAT, functional, regression, and integration testing across core banking, lending, and treasury systems, ensuring smooth workflows between Tableau, SAP, Moody’s Analytics, and third-party financial applications.
• Led a global QA team, overseeing test case development, defect triaging, sprint planning, and collaboration with Finance, Treasury, Risk, and IT teams to enhance system performance.
• Provided business process advisory, optimizing loan servicing, cost tracking, vendor payment processing, and financial reporting automation.

• Gathered and documented business requirements for fleet performance reporting and warranty fraud detection by collaborating with stakeholders, including fleet managers and operations teams.
• Conducted data analysis using SQL, Excel, and Python to assess fleet performance, maintenance trends, and fraud patterns in warranty claims.
• Designed and implemented automated KPI dashboards in Power BI to provide real-time insights on fleet utilization, fuel efficiency, and service costs.
• Created and optimized SQL queries to extract, transform, and analyze data from fleet management systems, ensuring accurate and timely reporting.
• Assisted in the development of predictive maintenance models, integrating IoT data from telematics systems to forecast vehicle service needs and reduce downtime.
• Conducted stakeholder workshops to define reporting requirements, ensuring alignment with business objectives and regulatory compliance.
• Developed functional specifications for integrating predictive maintenance insights into the fleet management system, improving decision-making.
• Provided data-driven insights to identify underperforming vehicles and optimize fleet operations.
• Designed and executed test plans, test cases, and test scripts for automated fleet reporting and fraud detection systems, ensuring data accuracy and system performance.
• Validated data pipelines and ETL processes by verifying SQL queries and automated scripts to ensure consistency between source and reporting data.
• Performed functional and regression testing on Power BI dashboards to ensure accurate visualization of fleet performance metrics.
• Utilized Python and SQL-based validation scripts to test data integrity in fleet management and fraud detection systems.
• Conducted performance testing using tools like JMeter to validate the efficiency of automated data refresh mechanisms.
• Automated data validation processes using Python scripts, reducing manual testing efforts by 60%.
• Ensured compliance with business rules and data governance policies for reporting and analytics solutions.
• Collaborated with developers, data engineers, and business stakeholders to troubleshoot defects and improve data accuracy in reporting systems.

• Supported enterprise-wide business analysis initiatives for commercial lending and wholesale banking.
• Built and maintained complex SQL queries for extracting insights from financial transactions.
• Engaged with developers to improve system efficiency and database performance.
• Analyzed customer and loan portfolio data to drive strategic business decisions.
• Assisted in migrating legacy financial systems to modern, distributed architectures.
• Developed Python scripts for automating repetitive data extraction and transformation tasks.