osilvahudson

1. Project: B2B digital platform connecting retailers and suppliers, streamlining orders and deliveries with innovative business tools. It operates in over 28 countries. 2. Main Achievements * Resolved performance issues in Azure and Databricks, reducing response time by 30%. * Gathered requirements with business teams, improving data accuracy by 25%. * Optimized data pipelines in MongoDB, reducing processing time by 20%. * Optimized pipelines in Databricks and Snowflake, increasing efficiency by 40% and reducing costs by 15%. 3. Tech stack Azure (Data Lake, Data Factory, Databricks) | Snowflake | DBT | Power BI | MongoDB | Jira | Python | SQL | Scala

1. Project: Global mining leader, focusing on iron, nickel, and copper production with a commitment to sustainability. 2. Main Achievements * Implemented a Data Warehouse on Snowflake and automated transformations with DBT, improving query performance by 40%. * Improved data quality by 15% by developing dimensional data models. * Automated data pipelines with CI/CD on Azure, reducing integration time by 30%. * Enhanced business alignment by translating requirements into technical solutions, boosting efficiency by 20%. * Managed data infrastructure with over 150 TB of data processed daily. 3. Tech stack Azure (Data Lake, Data Factory, Databricks, DevOps) | Snowflake | DBT | CI/CD | Data Modeling | Terraform | Power BI | Business Analysis | Python | SQL | Scala

1. Project: Brazilian startup specializing in Big Data, Internet of Things, Artificial Intelligence and Data Analytics solutions listed on Nasdaq valued at US$ 1 billion. 2. Main Achievements * Evaluated and tested new features of the Semantix data platform, increasing feature adoption by 30%. * Used GCP and tools such as Hive and Trino to optimize queries, resulting in performance improvements of 25%. * Introduced Kubernetes for container orchestration, reducing deployment time by 40%. * Led the evaluation and adoption of new data technologies, enhancing data engineering capabilities and improving overall system performance by 40%. 3. Tech stack Google Cloud Platform (Storage, Dataflow, Composer, Google Kubernetes Engine, BigQuery, Dataproc) | Python | Spark | Snowflake | Scala | SQL | Airflow | Kafka | DBT | Hive | Trino | Hadoop | Agile Methodology (Scrum) | DataHub Data Catalog | Open Metadata | Erwin Data Modeler | Talend Open Studio

1. Project: Brazil's largest construction and real estate company. 2. Main Achievements * Orchestrated the migration of the data pipeline from Python Pandas to PySpark, reducing processing time by 40%. * Leveraged Azure services for scalable cloud solutions, eliminating bottlenecks and increasing productivity by 30%. * Reduced data latency by over 50% by optimizing cloud infrastructure. 3. Tech stack Azure (Data Lake Storage, Data Factory, Synapse Analytics, AKS, Azure DevOps) | Python | Spark | SQL Server | Power BI | CI/CD Pipelines | Airflow | Docker | Hadoop | Scala | SSIS | SSMS | Business/Data Analysis | Erwin Data Modeler | Sharepoint | SQL

1. Project: Operated in credit recovery and customer service, as well as outsourcing business processes. 2. Main Achievements * Developed a scalable architecture, supporting data growth of 200% without loss of performance. * Reduced storage costs by 30% with optimization and compression in the data lake. * Led the migration to the cloud, reducing queries by 50% and facilitating real-time access. * Implemented data governance policies and security processes, ensuring compliance with GDPR and LGPD, improving data security and integrity by 30%. * Established data quality assurance processes, improving data accuracy and consistency by 25% and reducing integration errors by 40%. 3. Tech stack Azure (Data Lake Storage, Data Factory, Synapse Analytics, AKS, Azure DevOps) | Python | Spark | SQL Server | Power BI | CI/CD Pipelines | Airflow | Docker | Hadoop | Scala | SSIS | SSMS | SSAS | Business/Data Analysis| Erwin Data Modeler | Sharepoint

1. Project: Entity maintained by the companies Samarco, BHP Billiton and Vale, responsible for mobilizing to repair the damage caused by the rupture of the Fundão dam, in Mariana (MG/Brazil). 2. Main Achievements * Developed data architecture on AWS, increasing productivity and reducing response time by 500%. * Aligned requirements across 5 systems using AWS, Kafka, and PostgreSQL. * Led a team of 4 engineers, managing agile projects and ensuring on-time deliveries. * Enhanced data security by implementing encryption at rest and in transit. * Boosted productivity by 20% by mentoring junior engineers. * Processed high-volume data streams by implementing real-time data architecture with Apache Kafka. * Achieved 99.9% data accuracy by utilizing automated validation processes in data pipelines. 3. Tech stack AWS (S3, EC2, Redshift, Glue, QuickSight, RDS, EMR) | Python | Spark (Scala, PySpark) | PostgreSQL | Kafka | Hadoop | CI/CD Pipelines | Talend Open Studio | Pentaho Data Integration | Git | API’s | Erwin Data Modeler | Agile Methodology (Scrum)