Bruno is a Senior Data Engineer/Architect with over 6 years of professional experience focusing on Data engineering and analysis. He is an advanced developer of Spark and Scala and has worked extensively with Python as well. He has built and supported Cloud data solutions in both AWS and GCP, and is strongest with AWS tools, particularly with Kubernetes and related technologies. Bruno is a passionate technologist that is always learning new technologies and mastering best practices. Recently he has been studying data algorithms, trade-offs of different types of databases, and how to move from a batch-centric approach to an event-driven one, especially trying to apply the concepts of Data Products and Data Mesh.
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Main role is to negotiate and define data products, features, and topology alongside business domains. Specifying how to ingest, process and aggregate data. Coding frameworks, pipelines or database creations, while helping define standards for the data platform.
Stack: AWS, Kubernetes, Spark, Scala, Python, ksqlDB, MongoDB, REST API
Fraud data engineer responsible for defining the fraud data flow (ingestion, processing, storage) based on business requirements. Responsible for moving machine learning models into production (creating pipelines or Rest APIs to deploy the models) and mentoring junior engineers.
Stack: AWS, Kubernetes, Kubeflow, Spark, Scala, Python, Clojure, REST API, Machine Learning
Defined the architecture and implementation of data products, i.e., recommendation platform, end-to-end. Developed data pipelines and deployment of ML models into production.
Stack: AWS, Spark, Python, Terraform, Git, Airflow, Docker, Kubernetes, MLFlow, Machine Learning
Created data pipelines, and deployed ML models into production end-to-end.
Stack: Azure, Spark, Python, AirFlow, Machine Learning
Business Intelligence Analyst, responsible for collecting businesses requirements and converting into managerial dashboards (Power BI)