Wesley Chedlovski

I act as the technical bridge between data engineering and financial operations (FinOps). My core focus is ensuring data integrity, strengthening compliance, and reducing operational costs through systemic automation and analytical intelligence. 🎯 Financial Impact & FinOps: - Recovery & Efficiency: Structured automated invoice auditing routines that generated over BRL 5 million in cost savings. Recently, I mapped contractual gaps in operational workflows using Advanced SQL and Python, identifying financial recovery opportunities exceeding BRL 7.5 million. - Technical Leadership & Data-driven Culture: Provide operational guidance and analytical support for over 50 collaborators, replacing manual bottlenecks with scalable solutions and fostering the adoption of data-driven processes across the operation. ⚙️ Data Engineering & Automation: - ETL / ELT Pipelines: End-to-end architecture and maintenance of data processing pipelines, consuming and integrating complex billing, contract, and electrical energy databases through the Microsoft ecosystem (SharePoint and Excel). - Process Automation: Developed systemic workflows using Power Automate and Python scripts to automate critical back-office routines, increasing accuracy while drastically reducing operational risk and manual effort. 📊 Business Intelligence (BI) & Governance: - Enterprise Analytics: Developed executive dashboards and interactive reports in Power BI for KPI monitoring and strategic decision-making. - Governance: Built robust data models using DAX and Power Query, implementing Row-Level Security (RLS) to ensure the confidentiality and governance of corporate information.

Technical leadership of a financial squad focused on data auditing, governance, and operational efficiency. Acted directly at the intersection of finance and technology, translating analytical needs into technical solutions to support budget management. 🎯 Financial Impact & Compliance: - Risk Mitigation: Mass cross-referencing of contracts, payments, and structured databases to identify strategic cost-reduction opportunities and mitigate operational and fiscal risks. - Operational Governance: Continuous strengthening of internal controls and corporate financial compliance, ensuring data quality, consistency, and integrity across audits. ⚙️ Business Intelligence & Data Analysis: - Modeling & Reporting: Developed analytical reports and executive dashboards in Power BI, utilizing Power Query and DAX for precise monitoring of financial KPIs. - Structured Analysis: Frequent use of SQL and Advanced Excel for exploratory data analysis, transformation, and consolidation of large volumes of budgetary data.

Focused on extracting, processing, and transforming raw data into actionable insights for executive leadership. Centered on market intelligence and data analysis to support strategic decisions and high-value corporate negotiations. 🎯 Impact & Strategic Vision: - Optimization & Savings: Conducted asset benchmarking and contractual data analysis, identifying direct opportunities for financial adjustments and cost savings in complex negotiations and acquisitions. - Stakeholder Management: Delivered executive reports and market intelligence to senior management, driving data-driven decision-making and empowering business teams. ⚙️ Exploratory Analysis & Business Intelligence: - Data Processing: Extracted and consolidated large volumes of financial and market data using Advanced Excel and Exploratory Data Analysis (EDA) techniques. - Executive Reporting: Developed structured reports for the continuous tracking of financial KPIs and analytical support for the business.

Specialization focused on cloud data infrastructure, automation, and analytical pipeline orchestration. The program delves into developing scalable architectures and integrating Machine Learning and AI solutions across multicloud environments (AWS, Azure, and GCP). ⚙️ Study Focus & Practical Application: Cloud & Automation: Infrastructure as Code (IaC), CI/CD, Docker, and scalable environment orchestration for Data Engineering. Artificial Intelligence (AI): MLOps integration and exploration of advanced AI platforms to optimize operational workflows and technological development.

Degree focused on Data Engineering, relational modeling, large-scale data processing, and analytical architecture. Practical development aimed at solving complex business problems through data-driven solutions. ⚙️ Study Focus & Practical Application: Data Engineering & Databases: Dimensional and relational modeling, data architecture, and extensive proficiency in Advanced SQL (MySQL, PostgreSQL, SQL Server). Data Analytics & BI: Development and automation using Python, combined with Business Intelligence expertise (Microsoft Power BI, SSRS) to create interactive reports and support strategic decision-making.

Analytical degree with a strong emphasis on corporate financial operations, budgetary control, and project feasibility. The fundamental basis for FinOps roles, translating accounting and market complexity into actionable business insights. 📊 Study Focus & Practical Application: Banking Operations & Markets: Extensive knowledge of financial markets, foreign exchange operations, financial mathematics, and credit/collection analysis. Compliance & FinOps: Corporate financial statement analysis, technology project feasibility (ROI), financial risk management, and applied controllership.