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Daniel Romero
Platform Engineer at DNSFilter
Fortaleza, Brazil
I started my career as a sysadmin, configuring and maintaining bare-metal Linux servers. Then I closely followed the adoption of virtualization in servers and, later, the containerization process. Over the years, I acquired new skills to work as a software engineer, starting with PHP, Java, and then Ruby. I’ve kept myself updated and unlocked new skills, working with Terraform, Ansible, Docker, and Kubernetes. I can comfortably work with AWS, Google Cloud, and Azure. Now, I have started a new journey, exploring the fields of Data Science and Machine Learning. Check out my portfolio: https://infoslack.pro/
CodersRank Score
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This represents your current experience. It calculates by analyzing your connected repositories. By measuring your skills by your code, we are creating the ranking, so you can know how good are you comparing to another developers and what you have to improve to be better
Information on how to increase score and ranking details you can find in this blog post.
521.2
CodersRank Rank
Top 2%
Associate
Developer
Ruby
Associate
Developer
Go
Top 50
Python
Developer
Brazil
Highest experience points: 0 points,
0 activities in the last year
JSON
30.7
exp.
JavaScript
21.1
exp.
HTML
48.2
exp.
Ruby
20.2
exp.
CSS
10.2
exp.
Python
278.7
exp.
Jupyter Notebook
53.8
exp.
Shell
24.4
exp.
List your work history, including any contracts or internships
DNSFilter
Jun 2022 - Present (2 years 5 months)
Platform Engineer
Henku
Apr 2021 - Jun 2022 (1 year 2 months)
Data Scientist • Machine Learning Engineer
I worked to improve the data quality and helped with the automation of ML model training as well as the observability of the models. I participated in projects developing Machine Learning models to solve classification and regression problems with Scikit-Learn and deep learning problems with TensorFlow.
With the data science team, I applied and generalized statistical models to large datasets with Python, Scikit-Learn, and a lot of SQL. Other activities I got involved in were: Construction of production pipelines for ML using Airflow, Kubeflow, and SageMaker (implementing continuous training).
With the data science team, I applied and generalized statistical models to large datasets with Python, Scikit-Learn, and a lot of SQL. Other activities I got involved in were: Construction of production pipelines for ML using Airflow, Kubeflow, and SageMaker (implementing continuous training).
Elastic
Sep 2018 - Apr 2021 (2 years 7 months)
Senior Site Reliability Engineer
As an SRE, my main job was to provide a low latency response to incidents and service instability at many cloud providers (AWS, GCP, Azure) on the cloud team. Besides, I contributed to the tools, automation, and system engineering efforts using Ansible, Terraform, Docker, Python, and Golang.
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