11/05/2026 updated
100 % available
Data platform engineer
Madrid, Spain
Only remote
Master of Science in Biomedical Engineering, Politecnico di MilanoSql Data WarehouseApache AirflowBusiness Intelligence DevelopmentCloud EngineeringData ArchitectureData InfrastructureData TransformationData Transformation ServicesData WarehousingDevOpsDataOpsDatabase EnginesWorkflowsDatadogBusiness Intelligence Development Studio
Cloud & Data Infrastructure (AWS, Snowflake)
Extensive experience building and maintaining complex cloud architectures on AWS, including data warehousing on Snowflake with RBAC and IaC management, near real-time and batch ingestions using DBT and Airflow.
Data Pipeline Engineering
Design, implementation and industrialization of data pipelines for various sources, including reverse ETL, micro batch pipelines, incremental data validation patterns, and cost optimization for Snowflake and S3.
Software Engineering & API Development
Development and deployment of APIs using FastAPI and Rust for improved performance, real-time event processing with Flink for streaming solutions, and contribution to architectural design of complex projects.
Programming Languages (Python, Rust, Scala, SQL)
Proficiency in multiple programming languages including Python, Rust, Scala, and SQL, applied across data engineering, software development, and data platform projects.
Container Orchestration & DevOps (Docker, Kubernetes, Terraform)
Hands-on experience with Docker, Kubernetes, and Terraform for infrastructure as code, container orchestration, and CI/CD pipeline management including migration of Airflow hosting from Rancher to Kubernetes.
Workflow Orchestration (Airflow, DBT)
Implementation and management of Airflow for workflow orchestration and DBT for SQL transformations in data warehouses, streamlining data science workflows and supporting BI and analytics teams.
Monitoring & Observability (Datadog, Jenkins)
Improvement of services monitoring, alerting, and CI/CD pipelines using tools such as Datadog and Jenkins to ensure reliability and performance of data platforms.
Machine Learning & Deep Learning
Led a deep learning project using Convolutional Neural Networks and gradCAM algorithms for interpreting tumor classification genetic markers as part of a Master Thesis.
IoT & Sensor Data (Arduino, PowerBI)
Deployment of sensor fleets to enhance data transmission to warehouses, and use of PowerBI for data visualization, applied in end-to-end data architecture for industrial environments.
Extensive experience building and maintaining complex cloud architectures on AWS, including data warehousing on Snowflake with RBAC and IaC management, near real-time and batch ingestions using DBT and Airflow.
Data Pipeline Engineering
Design, implementation and industrialization of data pipelines for various sources, including reverse ETL, micro batch pipelines, incremental data validation patterns, and cost optimization for Snowflake and S3.
Software Engineering & API Development
Development and deployment of APIs using FastAPI and Rust for improved performance, real-time event processing with Flink for streaming solutions, and contribution to architectural design of complex projects.
Programming Languages (Python, Rust, Scala, SQL)
Proficiency in multiple programming languages including Python, Rust, Scala, and SQL, applied across data engineering, software development, and data platform projects.
Container Orchestration & DevOps (Docker, Kubernetes, Terraform)
Hands-on experience with Docker, Kubernetes, and Terraform for infrastructure as code, container orchestration, and CI/CD pipeline management including migration of Airflow hosting from Rancher to Kubernetes.
Workflow Orchestration (Airflow, DBT)
Implementation and management of Airflow for workflow orchestration and DBT for SQL transformations in data warehouses, streamlining data science workflows and supporting BI and analytics teams.
Monitoring & Observability (Datadog, Jenkins)
Improvement of services monitoring, alerting, and CI/CD pipelines using tools such as Datadog and Jenkins to ensure reliability and performance of data platforms.
Machine Learning & Deep Learning
Led a deep learning project using Convolutional Neural Networks and gradCAM algorithms for interpreting tumor classification genetic markers as part of a Master Thesis.
IoT & Sensor Data (Arduino, PowerBI)
Deployment of sensor fleets to enhance data transmission to warehouses, and use of PowerBI for data visualization, applied in end-to-end data architecture for industrial environments.
Experience
Professional experience5 - 10 years
Freelancer since2023
Languages
EnglishFluentFrenchNative speakerSpanishGood
Project history
Sole technical co-founder, designed and built the first version of the platform. Iterated, improved and added features based on first customers feedback.
Designed and optimized pipelines to acquire and process alternative datasets.
Developed and deployed APIs using FastAPI and Rust for improved performances. Implemented real-time event processing with Flink for streaming solutions. Built complex projects with multiple cloud components on AWS. Contributed to architectural design of various projects. Improved services monitoring, alerting and CICD pipelines. Maintained a data warehouse on Snowflake including RBAC and IaC management with near real-time and batch ingestions using DBT and Airflow. Worked closely with the data science team to industrialize their models. Technologies: AWS, Snowflake, Flink, Docker, Terraform, Serverless, Jenkins, Datadog, Airflow, DBT.