anujose Jose

<ul><li>Worked with daily sales, stock, and POS data to maintain accurate inventory levels and reduce discrepancies during busy trading periods.​</li><li>Analysed customer queries and purchasing patterns on the shop floor to support better product placement and service quality.​</li><li>Ensured compliance with store processes and health and safety standards while consistently meeting performance and customer‑service targets.</li></ul><p></p>

<ul><li>Performed end‑to‑end ETL on CRM and sales datasets, improving data consistency and reliability for real‑time dashboards and downstream reporting.​​</li><li>Built Tableau dashboards for revenue, retention, and engagement KPIs, reducing manual reporting time and improving visibility of commercial performance.​​</li><li>Implemented SQL‑based data validation on customer lifecycle data, reducing inconsistencies and increasing accuracy of reference and transactional datasets.​​</li><li>Used Python (Pandas, NumPy) for data cleaning, feature preparation, and anomaly detection to support churn and retention analytics.​​</li><li>Conducted EDA to identify customer patterns and contributed insights that informed engagement strategies and operational KPIs.​​</li><li>Standardised automated reporting templates and documentation to streamline weekly executive reviews and recurring BI reports.</li></ul><p></p>

<p>Performed end-to-end ETL processes on structured CRM and sales datasets, ensuring high data quality for real-time reporting.<br>
Built interactive Tableau dashboards visualizing revenue trends, retention metrics, and engagement KPIs, reducing manual reporting time by 40%.<br>
Implemented SQL-based data validation checks that decreased data inconsistencies by 18% across customer lifecycle datasets.<br>
Applied Python (Pandas, NumPy) for data cleaning, anomaly detection, and feature preparation for analytical models.<br>
Conducted EDA to identify patterns in churn and retention, contributing to a 12% improvement in customer engagement strategies.<br>
Created automated reporting templates to streamline weekly executive reviews.<br>
Presented data insights to stakeholders using clear, concise storytelling tailored to non-technical leadership.</p>

<p>Led QA and data validation initiatives for ERP systems handling large-scale engineering, geotechnical, and projectmonitoring datasets.<br>
Designed and executed functional, regression, and integration testing across data-heavy reporting and analytics modules.<br>
Developed Selenium automation scripts integrated into Azure DevOps CI/CD pipelines, reducing regression cycles by 35%.<br>
Performed SQL-driven data accuracy checks on KPI dashboards and reporting pipelines, improving release accuracy by 30%.<br>
Collaborated with data, product, and engineering teams to refine acceptance criteria and enhance analytical reporting workflows.<br>
Produced quality metrics and dashboards enabling data-driven go/no-go release decisions.<br>
Mentored junior QA engineers on ETL testing, SQL validation, and automation best practices.</p>

Led QA and data validation initiatives for ERP systems handling large-scale engineering, geotechnical, and project monitoring datasets, Designed and executed functional, regression, and integration testing across data-heavy reporting and analytics modules, Developed Selenium automation scripts integrated into Azure DevOps CI/CD pipelines, reducing regression cycles by 35%, Performed SQL-driven data accuracy checks on KPI dashboards and reporting pipelines, improving release accuracy by 30%, Collaborated with data, product, and engineering teams to refine acceptance criteria and enhance analytical reporting workflows, Produced quality metrics and dashboards enabling data-driven go/no-go release decisions, Mentored junior QA engineers on ETL testing, SQL validation, and automation best practices

<p>Executed end-to-end testing across finance, supply chain, and logistics modules used for analytics and operational reporting.<br>
Automated smoke tests using Selenium WebDriver, increasing test coverage by 25%.<br>
Conducted SQL validation for transactional and inventory data to support accurate dashboarding and MIS reporting.<br>
Improved defect resolution time by 20% through structured root cause analysis.<br>
Supported UAT cycles with business teams ensuring readiness of analytics workflows before deployment.</p>

<ul><li>Tested finance, supply chain, and logistics modules feeding operational and MIS dashboards, ensuring integrity of KPIs and performance metrics.​​</li><li>Automated smoke tests using Selenium and supported faster, more reliable releases for reporting functionality.​​</li><li>Performed SQL validation on transactional and inventory data to support accurate management reporting.</li></ul><p></p>

<p>Performed functional, workflow, and data migration testing across healthcare ERP modules.<br>
Validated large volumes of patient, billing, and insurance data for accuracy and regulatory compliance.<br>
Identified data discrepancies and improved healthcare workflow accuracy by 18% through targeted testing and RCA.<br>
Executed SQL-based backend data checks to validate data flow between integrated hospital systems.<br>
Created reusable regression test suites supporting consistent release quality.</p>

<ul><li>Performed functional and data migration testing across healthcare ERP modules with high‑volume patient, billing, and insurance data.​​</li><li>Validated large datasets and identified data discrepancies, improving workflow and reporting accuracy.​​</li><li>Executed SQL‑based backend checks to ensure correct data flow between hospital systems and reporting layers.</li></ul><p></p>