08/16/2025 updated
100 % available
Data Scientist and Engineer
Coimbra, Portugal
Only remote
Integrated Master in Aerospace EngineeringAgricultureApache HTTP ServerBusiness LogicArchitectureMicrosoft AzureBankingBusiness AdministrationCall CentersSoftware QualityContinuous IntegrationConvex OptimizationCryptographyData DeduplicationInformation EngineeringData Governance
Led multiple end-to-end data engineering and data science projects across industries including banking, public sector, energy, call centers, and agriculture. Acted as tech lead for teams of up to 6 people, with responsibility for task delegation, performance reviews, and mentorship, leading to improvements in code quality and delivery speed.
Leadership & Strategy:
- Owned architecture and implementation of complex data and ML solutions, balancing performance, scalability, and security trade-offs.
- Initiated and drove development of internal frameworks, later adopted by other projects, significantly improving velocity.
- Led stakeholder engagement: gathered requirements, communicated technical strategies, trade-offs and results, and coordinated joint delivery.
Data Engineering:
- Designed and implemented ingestion platforms in PySpark + Azure Data Factory, with automatic metadata validation, deduplication, and multi-source extraction.
- Built flexible frameworks abstracting data engineering logic, enabling teams to focus on business logic instead of boilerplate.
- Designed and implemented data modelling (leveraging medallion and dimensional modelling).
DevOps + Infrastructure:
- Developed CI/CD pipelines on Azure DevOps.
- Designed Azure infrastructures (connecting with on-prem and with 3rd party platforms)
- Developed IaC with Terraform (including private link Databricks).
Optimization/Data Science:
- Built ML model for detecting products with incorrect labels.
- Developed company budget optimization that couples sales targets with optimal factory production using convex optimization.
- Developed fraud risk model for 10M entities.
- Implemented MLOps best practices (including CI/CD, monitoring and versioning of models).
Data Governance:
- Built utilities to manage business and technical metadata in Apache Atlas/Microsoft Purview.
- Setup and managed Unity Catalog for multiple projects.
- Implemented data masking/encryption and compliance with GDPR.
Leadership & Strategy:
- Owned architecture and implementation of complex data and ML solutions, balancing performance, scalability, and security trade-offs.
- Initiated and drove development of internal frameworks, later adopted by other projects, significantly improving velocity.
- Led stakeholder engagement: gathered requirements, communicated technical strategies, trade-offs and results, and coordinated joint delivery.
Data Engineering:
- Designed and implemented ingestion platforms in PySpark + Azure Data Factory, with automatic metadata validation, deduplication, and multi-source extraction.
- Built flexible frameworks abstracting data engineering logic, enabling teams to focus on business logic instead of boilerplate.
- Designed and implemented data modelling (leveraging medallion and dimensional modelling).
DevOps + Infrastructure:
- Developed CI/CD pipelines on Azure DevOps.
- Designed Azure infrastructures (connecting with on-prem and with 3rd party platforms)
- Developed IaC with Terraform (including private link Databricks).
Optimization/Data Science:
- Built ML model for detecting products with incorrect labels.
- Developed company budget optimization that couples sales targets with optimal factory production using convex optimization.
- Developed fraud risk model for 10M entities.
- Implemented MLOps best practices (including CI/CD, monitoring and versioning of models).
Data Governance:
- Built utilities to manage business and technical metadata in Apache Atlas/Microsoft Purview.
- Setup and managed Unity Catalog for multiple projects.
- Implemented data masking/encryption and compliance with GDPR.
Experience
Professional experience5 - 10 years
Freelancer since2023
Languages
EnglishFluentPortugueseNative speaker
Project history
Led multiple end-to-end data engineering and data science projects across industries including banking, public sector, energy, call centers, and agriculture. Acted as tech lead for teams of up to 6 people, with responsibility for task delegation, performance reviews, and mentorship, leading to improvements in code quality and delivery speed.
Leadership & Strategy:
- Owned architecture and implementation of complex data and ML solutions, balancing performance, scalability, and security trade-offs.
- Initiated and drove development of internal frameworks, later adopted by other projects, significantly improving velocity.
- Led stakeholder engagement: gathered requirements, communicated technical strategies, trade-offs and results, and coordinated joint delivery.
Data Engineering:
- Designed and implemented ingestion platforms in PySpark + Azure Data Factory, with automatic metadata validation, deduplication, and multi-source extraction.
- Built flexible frameworks abstracting data engineering logic, enabling teams to focus on business logic instead of boilerplate.
- Designed and implemented data modelling (leveraging medallion and dimensional modelling).
DevOps + Infrastructure:
- Developed CI/CD pipelines on Azure DevOps.
- Designed Azure infrastructures (connecting with on-prem and with 3rd party platforms)
- Developed IaC with Terraform (including private link Databricks).
Optimization/Data Science:
- Built ML model for detecting products with incorrect labels.
- Developed company budget optimization that couples sales targets with optimal factory production using convex optimization.
- Developed fraud risk model for 10M entities.
- Implemented MLOps best practices (including CI/CD, monitoring and versioning of models).
Data Governance:
- Built utilities to manage business and technical metadata in Apache Atlas/Microsoft Purview.
- Setup and managed Unity Catalog for multiple projects.
- Implemented data masking/encryption and compliance with GDPR.
Leadership & Strategy:
- Owned architecture and implementation of complex data and ML solutions, balancing performance, scalability, and security trade-offs.
- Initiated and drove development of internal frameworks, later adopted by other projects, significantly improving velocity.
- Led stakeholder engagement: gathered requirements, communicated technical strategies, trade-offs and results, and coordinated joint delivery.
Data Engineering:
- Designed and implemented ingestion platforms in PySpark + Azure Data Factory, with automatic metadata validation, deduplication, and multi-source extraction.
- Built flexible frameworks abstracting data engineering logic, enabling teams to focus on business logic instead of boilerplate.
- Designed and implemented data modelling (leveraging medallion and dimensional modelling).
DevOps + Infrastructure:
- Developed CI/CD pipelines on Azure DevOps.
- Designed Azure infrastructures (connecting with on-prem and with 3rd party platforms)
- Developed IaC with Terraform (including private link Databricks).
Optimization/Data Science:
- Built ML model for detecting products with incorrect labels.
- Developed company budget optimization that couples sales targets with optimal factory production using convex optimization.
- Developed fraud risk model for 10M entities.
- Implemented MLOps best practices (including CI/CD, monitoring and versioning of models).
Data Governance:
- Built utilities to manage business and technical metadata in Apache Atlas/Microsoft Purview.
- Setup and managed Unity Catalog for multiple projects.
- Implemented data masking/encryption and compliance with GDPR.
Controlling, maintenance, and development of Blue Prism robots.
Development of automation and analytics tools to enhance the team framework with Python, SQL, and Powershell (production problem monitoring dashboard, software releases tool, version control tool, automatic maintenance ticket generator).
Working with banking client.
Development of automation and analytics tools to enhance the team framework with Python, SQL, and Powershell (production problem monitoring dashboard, software releases tool, version control tool, automatic maintenance ticket generator).
Working with banking client.
Working on predicting emergency rooms' waiting times using open data (social media, pollen and weather reports,...).