EstherAlexandra NgalebaZe

Overview: Contributed to data preparation and profiling efforts to ensure data quality for a large-scale data migration project, where cleansed and validated data were transferred to a new SAP platform.● Data Cleansing & Transformation: Leveraged advanced Excel functions (VLOOKUP, INDEX, MATCH, IF combined with AND/OR) to process customer and material master data, including customer contact information and product (raw, semi-processed, and finished goods) dimensions ensuring alignment with SAP standards. The cleansed data was subsequently uploaded into a staging area platform, which was later integrated into SAP.● Data Quality & Governance: Collaborated with the data governance team to maintain and validate a city master list (containing cities, regions, provinces, states, and countries). Ensured the data matched predefined SAP codes and was accurate, ensuring consistent data across multiple systems and preventing discrepancies in SAP migration.● Data Cleansing Standards & Automation: Assisted in the development of data cleansing rules to enforce consistency across datasets and improve overall SAP warehouse efficiency. This included defining standard processes for data validation, ensuring scalable, automated data processing workflows.● Data Analysis & Problem Resolution: Conducted data analysis to identify data quality issues, assess their scope, and develop effective solutions. Collaborated with relevant teams to implement fixes and optimize data pipelines for the SAP migration.● Issue Tracking & Collaboration: Used Jira to monitor data quality issues and assign tasks to relevant team members, ensuring quick and efficient issue resolution. This improved team collaboration and ensured that the data cleansing process was synchronized with SAP project milestones and data migration schedules.

Contributed to data preparation and profiling efforts to ensure data quality for a large-scale data migration project.
Cleansed and validated data transferred to a new SAP platform.
Leveraged advanced Excel functions (VLOOKUP, INDEX, MATCH, IF combined with AND/OR) to process customer and material master data.
Processed customer contact information and product dimensions, including raw, semi-processed, and finished goods, ensuring alignment with SAP standards.
Uploaded cleansed data into a staging area platform later integrated into SAP.
Collaborated with the data governance team to maintain and validate a city master list containing cities, regions, provinces, states, and countries.
Ensured the data matched predefined SAP codes and was accurate across multiple systems.
Assisted in the development of data cleansing rules to enforce consistency across datasets.
Improved overall SAP warehouse efficiency through standardized cleansing processes.
Defined standard processes for data validation to support scalable, automated data processing workflows.
Conducted data analysis to identify data quality issues and assess their scope.
Collaborated with relevant teams to implement fixes and optimize data pipelines for the SAP migration.
Used Jira to monitor data quality issues and assign tasks to relevant team members.
Ensured quick and efficient issue resolution.
Synchronized the data cleansing process with SAP project milestones and data migration schedules.

Overview: Designed and deployed end-to-end data pipelines to scrape and transform luxury watch listings from Chrono24, Crown & Caliber, and Analog Shift using Python-based tools (Selenium, Scrapy, BeautifulSoup). Orchestrated workflows with Apache Airflow (Docker) on AWS EC2 with Microsoft VS Code, storing cleaned data in S3 and PostgreSQL (via DBeaver), and integrated it into WatchCharts' pricing intelligence system alongside marketplace data from platforms like eBay.

Designed and deployed end-to-end data pipelines to scrape and transform luxury watch listings from Chrono24, Crown & Caliber, and Analog Shift.
Used Python-based tools including Selenium, Scrapy, and BeautifulSoup.
Orchestrated workflows with Apache Airflow on Docker.
Used AWS EC2.
Used Microsoft VS Code.
Stored cleaned data in S3 and PostgreSQL via DBeaver.
Integrated data into WatchCharts' pricing intelligence system alongside marketplace data from platforms like eBay.

Overview: Designed and implemented scalable data pipelines and ETL workflows that support the integration and transformation of large datasets within an enterprise data ecosystem.● Data Extraction & Integration: Extracted data from legacy systems and integrated it into a centralized data warehouse using SAP Data Services. Configured ETL jobs to efficiently transfer data and ensure smooth migration from legacy systems to the new platform.● Data Pipeline Development: Developed and optimized complex data workflows, to meet business requirements, leveraging SQL and SAP Data Services Designer (GUI) along with its built-in functions. This ensured the correct sequencing of ETL (extraction, transformation, and loading) operations across multiple data sources, enabling seamless and accurate data flow.● Data Transformation & Validation: Designed data flows that replicated ETL processes through SQL-based transformations, validating and cleansing incoming data to meet business rules. Developed data validation checks to ensure only accurate, consistent, and relevant data was loaded into target systems.● Automation & Workflow Orchestration: Automated data processing tasks and orchestrated workflows to streamline recurring data operations, reducing manual interventions and improving pipeline efficiency.● Testing & Debugging: Used SQL and Microsoft SQL Server to rigorously test and validate the robustness of data pipeline components, ensuring the stability and reliability of the data pipeline infrastructure. Performed unit tests on individual jobs and integration tests to verify seamless interaction between modules within the data pipeline.● System Integration: Executed IDOCs and configured job orchestration to ensure seamless data transfer between systems, specifically integrating SAP S/4 HANA into the larger data environment, enhancing system interoperability.

Designed and implemented scalable data pipelines and ETL workflows supporting integration and transformation of large datasets within an enterprise data ecosystem.
Extracted data from legacy systems and integrated it into a centralized data warehouse using SAP Data Services.
Configured ETL jobs to transfer data efficiently and support migration from legacy systems to the new platform.
Developed and optimized complex data workflows using SQL and SAP Data Services Designer.
Ensured correct sequencing of ETL operations across multiple data sources.
Designed data flows that replicated ETL processes through SQL-based transformations.
Validated and cleansed incoming data to meet business rules.
Developed data validation checks to ensure only accurate, consistent, and relevant data was loaded into target systems.
Automated data processing tasks and orchestrated workflows to streamline recurring data operations.
Reduced manual interventions and improved pipeline efficiency.
Used SQL and Microsoft SQL Server to test and validate data pipeline components.
Performed unit tests on individual jobs and integration tests between modules within the data pipeline.
Executed IDOCs and configured job orchestration to ensure seamless data transfer between systems.
Integrated SAP S/4 HANA into the larger data environment.

Overview: Led data cleansing initiatives and designed processes to improve data quality and operational efficiency within the Microsoft Dynamics CRM system, contributing to more accurate data management and reporting.● Data Cleansing: Cleansed and updated over 60K CRM records, collaborating with business stakeholders to ensure the accuracy and relevance of the data.● Data Deduplication & Consolidation: Developed and executed processes to identify and merge duplicate and obsolete CRM records, improving the integrity and usability of the database.● Collaboration for CRM Reporting: Worked closely with developers to design and configure custom CRM reports that provided real-time insights into data health.● Data Quality Monitoring & Dashboard Development: Supported the creation and maintenance of an Excel data quality dashboard, enabling stakeholders to track the progress of the data cleaning project and measure improvements over time.● Documentation & Process Improvement: Documented the data cleaning procedures and best practices, creating reusable guides to streamline future data management efforts. Developed templates and workflows for ongoing data maintenance, ensuring long-term consistency and quality.

Cleansed and updated over 60K CRM records.
Collaborated with business stakeholders to ensure the accuracy and relevance of the data.
Developed and executed processes to identify and merge duplicate and obsolete CRM records.
Improved the integrity and usability of the database.
Worked closely with developers to design and configure custom CRM reports.
Supported the creation and maintenance of an Excel data quality dashboard.
Enabled stakeholders to track the progress of the data cleaning project and measure improvements over time.
Documented the data cleaning procedures and best practices.
Created reusable guides to streamline future data management efforts.
Developed templates and workflows for ongoing data maintenance.
Ensured long-term consistency and quality.

Overview: Led database cleansing efforts to optimize customer data management within an SAP-powered CRM platform, ensuring data quality, system efficiency, and actionable insights for marketing and sales teams.● Data Quality Management & Data Cleaning Project Planning: Designed and implemented a comprehensive data cleaning strategy for the CRM system, identifying data issues, establishing resolution methods, and defining quality metrics. Automated the monitoring of data quality, ensuring visibility and timely reporting for stakeholders and enabling ongoing improvements.● Project Leadership & Resource Management: Managed a cross-functional team through all stages of the data cleaning project, utilizing project management methodologies to allocate tasks, estimate costs, and manage resources. Ensured project milestones and deadlines were met while staying within budget, optimizing both human and technical resources.● Data Collection & Preparation: Created documentations, to gather sales related information from dealers, and used them, in collaboration with affiliated agencies, to update the CRM virtually eliminating data issues associated with approx. 20K fields within the database which positively affected dealers’ KPIs.● Data Integration: Updated 100K+ clients’ information in SAP by integrating external data sources to update empty fields, enhance marketing communication and sales compensation process.● Data Pipeline Optimization & Workflow Automation: Re-engineered notification workflows to automate and streamline the flow of customer inquiries from online platforms to Porsche Centers. Optimized processes to reduce lag time and enhance real-time data updates, improving customer engagement.● Advanced Analytics & Segmentation: Leveraged SAP HANA to perform client segmentation and generate actionable insights for decision-making.● Reporting & KPI Dashboards: Developed dashboards with Excel and PowerPoint that showcased KPIs and work progress related to the data cleaning project. Presented reports and insights to management, sales teams, and external stakeholders, facilitating informed decision-making.● System Configuration & Data Enrichment: Configured CRM fields to enrich data and improve lead status tracking, enhancing sales forecasting and performance analysis.● Documentation & Knowledge Sharing: Created comprehensive documentation and guides in English and French, detailing CRM best practices and usage tips. Published guides through company newsletters and shared insights through presentations to sales teams, promoting better data management practices and improving overall data quality.

Designed and implemented a comprehensive data cleaning strategy for the CRM system.
Identified data issues, established resolution methods, and defined quality metrics.
Automated the monitoring of data quality.
Ensured visibility and timely reporting for stakeholders.
Managed a cross-functional team through all stages of the data cleaning project.
Allocated tasks, estimated costs, and managed resources using project management methodologies.
Ensured project milestones and deadlines were met while staying within budget.
Created documentations to gather sales related information from dealers.
Updated the CRM in collaboration with affiliated agencies.
Virtually eliminated data issues associated with approximately 20K fields within the database.
Updated 100K+ clients’ information in SAP by integrating external data sources.
Enhanced marketing communication and sales compensation process.
Re-engineered notification workflows to automate and streamline the flow of customer inquiries from online platforms to Porsche Centers.
Optimized processes to reduce lag time and enhance real-time data updates.
Improved customer engagement.
Leveraged SAP HANA to perform client segmentation and generate actionable insights for decision-making.
Developed dashboards with Excel and PowerPoint that showcased KPIs and work progress related to the data cleaning project.
Presented reports and insights to management, sales teams, and external stakeholders.
Configured CRM fields to enrich data and improve lead status tracking.
Enhanced sales forecasting and performance analysis.
Created comprehensive documentation and guides in English and French detailing CRM best practices and usage tips.
Published guides through company newsletters and shared insights through presentations to sales teams.
Promoted better data management practices and improved overall data quality.

Overview: Meticulously analysed, stored, and structured data related to installed products within Salesforce, ensuring it was organized for easy access and retrieval. This effort was aimed at supporting the broader organization's objectives, enabling more informed decision-making and helping drive the achievement of key business goals.● Data processing: Performed data analysis, data cleansing, and generated reports on large datasets.● Report generation: Developed reports using Salesforce and MS Excel Pivot Tables to track data updates and cleaning progress.● Data extraction: Developed data extraction strategies from multiple sources and tools to capture relevant data.● Stakeholder collaboration: Collaborated with regional IB leads to evaluate data requirements, identify gaps, and assess progress towards data-driven objectives.● Data update documentation: Created document showcasing procedures to follow to accurately update data.

Performed data analysis, data cleansing, and generated reports on large datasets.
Developed reports using Salesforce and MS Excel Pivot Tables to track data updates and cleaning progress.
Developed data extraction strategies from multiple sources and tools to capture relevant data.
Collaborated with regional IB leads to evaluate data requirements, identify gaps, and assess progress towards data-driven objectives.
Created document showcasing procedures to follow to accurately update data.