As a Data Engineer in a multidisciplinary team, my role involves data modeling and the provisioning of customized architectures to meet the specific demands of each project, guaranteeing its integrity and efficiency. I always seek solutions that are scalability-oriented, economically viable and secure.Main highlights:>> I implemented a data architecture using Databricks as Software as a Service (Databricks Workflow, Unity Catalog, Databricks SQL) in a Big Data project, where all the data remodeling was done using Python and PySpark, decommissioning SAP BW and generating a 22% reduction in the annual cost of the data architecture.>> I led the data modeling for an on-premises Big Data project, using technologies such as Hadoop, Hive, Presto, Python and PySpark.

As a Data Analysis Engineer, I led the construction of ETL processes using tools such as Airflow and DBT to ensure data quality, efficiency and low cost. I developed optimized SQL queries in Snowflake and AWS Athena, as well as automating data pipelines with DAGs in Airflow. I also migrated legacy tables, integrated processes via APIs and used the AWS Cloud with version control in Git and GitHub.Main highlights:>> I developed the ETL process by incorporating the DBT tool into our stack, with the aim of improving data quality, increasing efficiency, scalability and ease of maintenance, as well as reducing processing costs by 8%.>> Implementation of an incremental update approach for datalake databases, resulting in a reduction of more than 30% in processing costs.

As an Analytics Engineer in a multidisciplinary team, I am responsible for creating Data Preparation Flows using Power Query and Python (ETL), as well as implementing Databases using the Python language. I structure table relationships within the database using Python and develop efficient SQL queries. In addition, I contribute to the creation of dashboards and KPIs in MS Power BI, using Dax and M, to offer valuable insights to stakeholders.Main highlights:>> Conducting the comprehensive structuring and consolidation of all the company's databases, with a focus on guaranteeing the integrity and accuracy of the information stored. By automating the data pipeline, the process is managed efficiently, reducing problems of inconsistency and guiding the company towards the effective adoption of a data-driven culture.>> Development of a preliminary forecasting study aimed at preventing customer losses, resulting in estimated revenue of R$200k per year.

As a Jr. Analytics Engineer, my responsibilities include automating the integration of data from the SAP MM system with Excel, using VBA. Performing data processing to evaluate the annual cost, financial useful life, MTBF (Mean Time Between Failure) and MTTR (Mean Time Between Repair) of the unit's assets. General reports are prepared using Power BI. Automating operational routines linked to the process of planning maintenance orders for the units.Main highlights:>> I developed an automated process that resulted in a significant 85% reduction in the time needed to generate reports on the unit's assets.

As a Financial Analyst, my responsibilities range from creating and applying indicators in the Pine Script language to consolidating and analyzing the results of daily operations. In addition, I manage KPIs related to Yield, Opportunity Risk, Average Operating Time, among others, seeking to automate the analysis of possible capital allocations using tools such as Excel.