Back-end Developer with over nine years of experience, currently focused on developing nanoservices and microservices and actively participating in technical discussions and decision-making processes. Possesses solid knowledge in Kotlin and Java, with practical experience in Spring and Micronaut frameworks. Additionally, skilled in developing serverless applications using Chalice in Python.

Angular and .NET Core Developer with five years of experience in specialized technologies and design patterns, including NGRX, RXJS, NGX-TRANSLATE, Lazy Loading, Angular I18n, D3.js, as well as SOLID principles, Domain-Driven Design (DDD), Facade pattern, and CQRS with Mediator.

System Analyst specializing in Java and Python development.

Front-End Developer with advanced proficiency in key development technologies, demonstrating a robust career of 44 years marked by significant contributions through innovation and efficiency. Specializes in dynamic web application development, leveraging JavaScript, TypeScript, and ReactJS, including functional components, to achieve high performance and adherence to best practices. Expert in using Next.js for server-side rendering to enhance SEO and loading speeds, along with adeptness in state management through Context API and Redux Toolkit.

Proficient in design and CSS, utilizing Tailwind CSS to create customized, responsive interfaces efficiently with its utility-first approach. Employs SASS/SCSS for more organized and efficient CSS coding, incorporating variables, mixins, and nesting. Develops styled components within React to improve code modularity and maintainability. Skilled in planning and designing user experiences in Figma, applying UX design principles to ensure both functionality and aesthetic appeal.

Possesses expertise in DevOps practices including the deployment of scalable, high-availability infrastructure with AWS services such as EC2, S3, RDS, and Lambda. Experienced in configuring and managing CI/CD pipelines using GitHub Actions and AWS CodePipeline to support agile development and continuous delivery. Familiarity with Docker and Kubernetes enhances consistency from development to production environments.

Software Engineer specializing in back-end technologies with a focus on Python Django, utilizing Django Rest Framework (DRF) and Django-CMS. Demonstrates a strong ability to thrive in team environments comprising diverse individuals. Assumes responsibility, leadership, and ownership of the product. Committed to continual learning and professional development.

Data Analyst with approximately two years of experience in Business Intelligence, specializing in Supply Chain analytics. Contributions include the development of various BI projects for fulfillment centers, transportation, and finance teams, which had a significant impact on business operations. Received recognition from the Supply Chain Director for outstanding contributions. Currently advancing skills towards becoming a Data Scientist, with ongoing studies in data science tools and statistical models.

An Information Technology Management graduate from FATEC, with a background in IT support and a specialization in .NET and C#. Through practical work experience, manual testing was explored, igniting a keen interest in Quality Assurance (QA). To augment this interest, an intensive QA course was completed, currently culminating in a role dedicated to software quality assurance.

Beginning my coding journey in 2015, I have since gained experience with a range of technologies, including Pascal, C, Python, Java, and C#. My core expertise lies in React Native, Node.js, AWS, and SQL. Over the course of my career, I have developed multiple React Native applications and Node.js REST APIs from the ground up, as well as overseen numerous projects. Currently, my professional focus is directed towards backend development, particularly using Node.js and AWS.

Google Cloud Video Intelligence is a service that uses machine learning to analyze video content. It can detect objects, activities, and scenes within videos, enabling users to search and categorize video data efficiently.

A Google Cloud Video Intelligence expert must have skills in machine learning, data analysis, and video processing. Proficiency in using Google Cloud Platform services, particularly APIs, is essential. Knowledge of programming languages such as Python and familiarity with video encoding and metadata extraction are also crucial.

How to hire a Google Cloud Video Intelligence expert

Google Cloud Video Intelligence was introduced by Google in 2017. It was developed to leverage machine learning for analyzing video content, allowing users to detect objects, activities, and scenes within videos for improved search and categorization.

About Google Cloud Video Intelligence

Strengths of Google Cloud Video Intelligence included advanced machine learning capabilities, accurate object detection, and robust scene analysis. Weaknesses involved potential high costs and occasional inaccuracies in complex video contexts. Competitors included Amazon Rekognition, Microsoft Azure Video Indexer, and IBM Watson Video Enrichment.

Google Cloud Video Intelligence

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About Google Cloud Video Intelligence

How to hire a Google Cloud Video Intelligence expert

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