I am a professional with 10 years of experience in Data Engineering, specializing in cloud data. I have worked across Agribusiness, Retail, and Media sectors, and I am fluent in English with AWS and Snowflake certifications. My expertise lies in developing and optimizing over 200 ETL/ELT pipelines across AWS, GCP, and Azure, with a strong focus on performance and scalability. I have proven results in automating critical processes, reducing execution time by up to 80%, and optimizing ML/DS pipelines by over 50%. I possess advanced experience with Python, SQL, Spark, Kafka, Airflow, Snowflake, BigQuery, and CI/CD practices such as GitHub Actions and Terraform. Additionally, I have strong skills in observability using Datadog, data governance (LGPD), and technical mentoring, which fosters maturity in DataOps and MLOps.
Optimized data pipeline performance for climatology workflows, developed and maintained ETL/ELT pipelines, automated deployment workflows, designed serverless pipelines, implemented observability, enhanced performance of analytical queries, improved reliability of pipelines, led development of hybrid ETLs, supported Data Science teams, mentored interns and team members.
Developed ETL/ELT pipelines in a multi-cloud environment, modernized forecasting process, reduced execution time of data science pipelines, created and managed Docker images, integrated massive data into Snowflake and Redshift.
Reduced execution time of legacy analytical reports, developed ETL/ELT pipelines for data ingestion, migrated and optimized queries from Oracle to BigQuery, managed and optimized processing of large data volumes.
MBA in Data Science & Analytics
Bachelor in Civil Engineering
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