Developer engineer with extensive experience in distributed systems and databases, transitioning towards data engineering and artificial intelligence. Passionate about data analysis and machine learning.
Duration
6 months
Date
As soon as possible
Objective
Deepen skills in data engineering and ML in a professional context
From Full Stack Engineering to Data & AI
My experience in full stack development, particularly in handling complex data flows and optimizing application performance, naturally led me to data engineering and AI. Building scalable applications gave me a strong foundation in data processing and system optimization.
My background in software engineering equipped me with crucial skills for data projects: structured problem-solving, efficient system design, and a deep understanding of data flows. This technical foundation allows me to bridge the gap between development and data science.
Leveraging my backend development experience to build robust data pipelines and optimize data processing workflows.
Using frontend development skills to create intuitive data visualizations and interactive analytics dashboards.
Applying system architecture knowledge to deploy scalable ML solutions and data processing pipelines.
From Software Engineering to Data Science
Identifying data analysis issues that offer the best opportunities to the organization; Determining appropriate datasets and variables; Collecting large structured and unstructured datasets from disparate sources; Cleaning and validating data to ensure accuracy, completeness, and uniformity; Designing and applying models and algorithms to exploit large data stocks; Analyzing data to identify patterns and trends; Interpreting data to discover solutions and opportunities; Communicating results to stakeholders using visualization and other means.
Development of e-commerce sites via WordPress and WooCommerce; Creation of mobile applications with React Native/Android Studio; Front-end and back-end development with ReactJS/AngularJS, PHP/NodeJS.
Development and updating of web features; Optimization of the deployment pipeline via Bitbucket, Amazon services; Onboarding of new developers; Integration of components and suggestions for improvements.
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