Ian Paulo Ruiz Collazos

 Design, development, and migration of ETL pipelines from SSIS to Fabric Data Pipelines, standardizing data ingestion and consolidating information into the corporate database.  Development of corporate dashboards in Power BI using independent connectors (Odoo, Jira, among others), incorporating DENEB (Vega/Vega-Lite), DAX, and Row-Level Security (RLS) to meet business and executive management requirements.  Administration and modeling of the corporate semantic model as a single source of truth, integrating multiple data sources and eliminating discrepancies across reports; the inventory module was deployed to production with no divergences.  Implementation of web scraping processes using Python and automated data loading via ETL into institutional servers.  Establishment of data quality controls (business rules, consistency validations, and duplicate checks), with lineage documentation, versioning, and change auditing using Git.  Development of a self-service telephony prototype (Python + Asterisk + F5-TTS via API), enabling the technological foundation for future AI-driven automated customer service use cases.  Evolutionary and corrective maintenance of Python code related to IFRS 9 and IAS 2, ensuring data integrity, regulatory alignment, and consistency across reports.  Comprehensive documentation and review of ETL processes associated with the corporation’s central database.  Data profiling and statistical analysis of the main information tables.  Handling and management of information request tickets from business user areas.  Automation of operational tasks using Power Automate.

 Lead migration of OLAP cubes from legacy systems to the modern Microsoft Fabric environment, designing a structured Data Warehouse and ensuring continuity of the dimensional model for financial and operational reporting.  Design and development of an end-to-end solution using Microsoft Fabric Lakehouse to manage data from an e-commerce system, ranging from the initial loading of Excel files to the generation of reports with Power BI.  Creation of data pipelines and PySpark notebooks to dynamically load data from various sources into data layers.  Cleaning and loading data using T-SQL to ensure consistency of records without duplicates and applying ETL strategies for mass data migration.  Implementation of relationships between FACT tables and dimensions in Fabric, simulating traditional OLAP models with a modern approach to analysis and queries, reflecting business models.  Designing advanced measures and calculations in Power BI connecting directly to the semantic model, enabling real-time queries with DirectQuery.

 Transformation and schematization of complex commercial system information into a clear and accessible format, providing Management and Business with a precise and detailed vision of internal Sales and Distribution processes (sales from Distributor partners and Pharmacy Chains), improving data quality and facilitating strategic decision-making.  Optimization of the Data Warehouse: Responsible for the detailed schematization of ETL processes related to Sales and Distribution systems, ensuring a clear understanding of the data flow from extraction to storage. Implemented improvements in data loading, eliminating redundancies and optimizing overall performance, simplifying audit processes and enabling the identification of operational improvement opportunities.  Analysis and optimization of stored procedures (Stored Procedures) in Sales and Distribution systems, documenting and optimizing transaction logic, table updates, and calculations. These improvements resulted in a significant reduction in processing times and increased efficiency in handling large volumes of data.  Schematization and analysis of OLAP cube structures, used for multidimensional data analysis, improving the clarity and understanding of dimensions and measures. This facilitated decision-making for end-users and provided tools for more efficient and accurate information analysis.

 Statistical analysis for the Business area: sales, distribution, and supply of agency-stores and E-commerce channel. Achieved increased sales by acquiring new customers (+2.5% monthly) and retaining the customer base.  KPIs: Responsible for identifying and anticipating deviations in Business KPIs, using Machine Learning, Deep Learning, and AI to develop predictive models that improve decision-making and increase business outcomes.  Turnover: Use of Data Science techniques to optimize inventory by redistributing collateral items among agency-stores.  Development of tools for commercial monitoring, driving an increase in placements and garment sales.  Automation of Weekly and Monthly Reports directed at senior management and the Board, presenting business progress through high-impact visual statistical charts, AI-assisted analysis for identifying improvement opportunities.  Programming for the creation and sending of automated daily graphical reports to agencies, showing progress in placements and sales, enabling agency managers to take early corrective and improvement actions.  Weekly coordination with Line Managers for monitoring and evaluating improvements.  Supervise activities aimed at ensuring the achievement of commercial goals assigned to sales channels.  Vehicle Credit Project: Process mapping. Requirement gathering for the new vehicle pawn credit product. Identification of criticality and complexity of activities, estimates. Prototyping and documentation of requirements in technical language for the provider. Successful execution of the pilot, from the first contact with the client to disbursement.

 Live translation for both English and Spanish native speakers around the world.  Business knowledge of diverse industries in the United States: Banking and Insurance and Finance, Healthcare, Government Services.  Effective management of interactions with clients from diverse cultures and backgrounds, with a high level of empathy and interpersonal communication skills in a multicultural and multilingual environment.

 Provide first and second level technical support (applications) to users (on-site and remote), ensuring timely responses and effective solutions at the first contact, minimizing downtime, maintaining high levels of satisfaction.  Generation of queries to meet specific information needs at the request of users (Oracle query database).  Coordinate the installation, configuration and maintenance of systems and applications.  Document procedures and solutions for internal knowledge and user training.

 Analysis of songs broadcasted in Lima without interruptions, generating radio broadcast indicators in Excel. This process required 50 hours per month from the Market Research area. Project: It is automated through Python and Artificial Intelligence technologies (neural networks and machine learning), reducing the audio processing time to 30 minutes, which facilitates its daily execution. In addition, Power BI is used to present indicators of song playback in the radio market and simplify the programming of songs in CRP stations.  Generation of reports on music trends for the Corporation's FM stations, YouTube, Spotify and Billboard.  Proposal of recommendations for the release of premiere songs to the 10 stations, applying data science techniques.  Automation of operational tasks: updating the playlists of each radio station according to the reception of the songs by the public.  Support in the development of business strategies to determine which products to offer to consumers.

Multinational company based in France. The company provides customer acquisition management, customer care, technical support, social media services and other services. It operates in 88 countries and serves 170 markets. Duties:  Customer base maintenance management.  Timely response to customer inquiries in various channels: calls, chats and emails (all in English).  Excellent communication skills in English to gain customer trust and loyalty.  First level technical support to users, diagnosing and resolving Windows and office automation problems, and assistance via phone, chat, email, remote access. Incident logging, management and escalation through the Gladly system.

 Supervision on the quality control and monitoring of several statistical models.  Contributed with the design of reports evaluating the Data Quality, Technological Environment, Implementation and Documentation of each of the models.  Performed statistical analysis on the Products/Business Segments, providing timely information to Management to improve decision making.  Improvement proposals in the KPIs used in Collections (Credit Lines and Consumer Credit, Mortgage), supporting the user areas in the implementation of the models through massive data processing and analysis.  Intensive use of Python and R programming languages.

Watch, monitor, prevent and attend, providing immediate response of water rescue to our clients, at risk situations in or around the indoor swimming pools.

Take care of the slides offering the best experience to clients, with safety and comfort at every moment.