Skip to content
View samuel-aka-viana's full-sized avatar

Organizations

@vot-Up

Block or report samuel-aka-viana

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 250 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
samuel-aka-viana/README.md

Samuel Viana

Data Engineer | Backend Developer


πŸ” About Me

Data Engineer with 4 years of experience developing data solutions and backend systems. I work professionally with data pipelines, microservices, and system modernization, always applying engineering best practices.

Professional Experience:

  • Development of data lakes and pipelines using PySpark, Airflow, and Databricks
  • System migration and database optimization (SQL Server β†’ PostgreSQL)
  • Microservices architecture and RESTful APIs with Django
  • Implementation of observability and monitoring in production
  • Technical mentoring and DevOps practices

Portfolio: My repositories demonstrate practical application of concepts I use daily, exploring modern technologies and sharing knowledge through technical projects.


πŸ› οΈ Technology Stack

πŸ’» Backend & Data Engineering

Python Django Apache Spark dbt Apache Airflow Prefect

☁️ Cloud & DevOps

AWS Terraform Docker Kubernetes Redis

πŸ“Š Data Stack

BigQuery DuckDB PostgreSQL Apache Superset Polars


πŸš€ Portfolio Projects

Practical demonstration of modern Data Warehouse architecture

  • Technologies: DLT, dbt, BigQuery, DuckDB, Apache Superset, Docker
  • Highlights: Medallion architecture implementation, automated testing, containerization
  • Purpose: Apply concepts used professionally in a creative and documented context

Serverless streaming pipeline simulation with local AWS environment

  • Technologies: Terraform, LocalStack, Prefect, Polars, Kinesis, S3
  • Highlights: Infrastructure as code, cloud environment simulation, orchestration
  • Purpose: Demonstrate knowledge in event-driven architectures and AWS technologies

Complete portfolio with experiments in data engineering, automation, and new technologies.


πŸ“ˆ Performance Metrics

stats graph languages graph

πŸ’Ό Technical Competencies

Data Engineering        β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ         80%
Backend Development     β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ      85%
DevOps & CI/CD          β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ             70%
Database Optimization   β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ         80%
Observability          β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ               65%

🎯 Professional Goals

  • Continue evolving in scalable and modern data architectures
  • Contribute to projects that integrate ML/AI in production pipelines
  • Expand knowledge in emerging technologies from the data ecosystem
  • Share knowledge through open source projects and mentoring

πŸ“§ Contact

Interested in discussing challenging data engineering opportunities? Explore my projects and let's talk about how I can contribute to your team!

LinkedIn Email Portfolio

Pinned Loading

  1. dlt-jaffle-shop dlt-jaffle-shop Public archive

    Python 1 1

  2. aws-terraform aws-terraform Public

    HCL 1

  3. deathmetal-dw deathmetal-dw Public

    Python 1