Emanuel Alexandre T.

Senior Database & Data Architecture Consultant | Businnes Intelligence

I am a senior database, data architecture, and BI consultant with 42 years of experience designing business systems, databases, data warehouses, integrations, and analytics solutions across industries such as retail, SaaS, healthcare, asset management, banking, manufacturing, services, e-commerce, and finance. My strongest value is connecting business needs with reliable technical architecture. I help clients move from scattered data, fragile reports, and manual processes to analytical environments that are fast, reliable, maintainable, and ready for BI or AI. Core strengths • Database architecture, SQL, performance tuning, and data modeling • Data warehouse design, ETL/ELT, and automated data pipelines • Power BI dashboards, semantic models, DAX, and Power Query • BigQuery, SQL Server, SingleStore, PostgreSQL, MySQL, Oracle, and Microsoft Fabric • Python, APIs, Google Cloud, AWS, Azure, and cloud-based data workflows • KPI definition, metric validation, executive reporting, and AI-ready data layers Unlike many dashboard-focused consultants, I come from a deep database and systems background. I design the structure behind the report: schemas, relationships, ETL routines, indexing strategy, validation rules, semantic models, and performance optimization. This helps clients avoid fragile dashboards built on messy data and instead create a solid data foundation for reporting, analytics, and AI. AI-ready data architecture Many companies try to connect AI directly to raw databases, but that often creates slow, expensive, and unreliable answers. My approach is different: I build governed analytical layers where definitions, relationships, KPIs, and business rules are explicit. This improves trust, reduces cost, increases performance, and allows AI to work with business-approved metrics rather than guessing from raw tables. Recent project examples - Database Performance / DBA Leadership I am responsible as DBA and Database Lead for a massive infrastructure using SingleStore and SQL Server, working at billion-record scale with the responsibility to deliver query results in less than 1 second. This involves database design, indexing strategy, stored procedures, and continuous optimization of high-volume workloads. - AI-Connected Semantic Model with Power BI and Claude I designed a cloud-based analytical solution using Cloud Run, Python, GitHub/Artifacts, Cloud Scheduler, BigQuery, and Power BI semantic models, enabling Claude to connect to governed business data. The solution included specialized skills to query the semantic model, respect business rules, and provide accurate answers with high performance and data reliability. - AI Data Enrichment on Google Cloud I designed and implemented a serverless AI enrichment pipeline using Google Cloud Run, Cloud Tasks, Cloud Scheduler, Python, and BigQuery. The client needed to enrich millions of company records using GROK AI within a tight processing window while controlling BigQuery costs. The result was millions of enrichment tasks completed within SLA, stable throughput, structured validation, and more than 90% reduction in BigQuery costs. - IoT Data Aggregation with BigQuery I built a Google Cloud solution to collect high-frequency sensor data from thousands of sensors through an API every three minutes. The architecture used Cloud Run, Python, GitHub/Artifacts, Cloud Scheduler, and BigQuery, creating an automated and scalable data warehouse process running for months without manual intervention. - SaaS Product Analytics For a SaaS company, I transformed complex Firebase / Firestore JSON data into structured analytical tables in BigQuery. I created the ETL routines, designed the analytical foundation, and delivered Power BI dashboards for product usage, engagement, trial behavior, feature adoption, and conversion analysis. - Retail Operations Reporting I built an automated reporting system for a large restaurant chain, processing POS data with Python ETL, cloud automation, AWS infrastructure, and Power BI applications. The system delivered daily KPI reporting for sales, revenue, labor, service times, customer behavior, and operational performance. - Asset Management Analytics I developed a portfolio monitoring solution using Python ETL, Reorg API, AWS, database design, and Power BI. The solution tracked liquidity, EBITDA, leverage, and other investment KPIs, giving the client daily updated information for portfolio analysis and decision-making.