About Trafilea Trafilea is a dynamic and innovative Tech E-commerce Group that operates multiple direct-to-consumer brands in the intimate apparel and beauty sectors, with a focus on using data-driven strategies to scale their businesses. In addition to our products, we have our own online community dedicated to promoting body positivity. As a rapidly growing global player, Trafilea is committed to creating high-quality products and services that enhance the customer experience and drive long-term growth.
Analysis, Design, implementation, and maintenance pipelines that produce business-critical data reliably and efficiently using cloud technologies.
Develop new ETLs (Extract, Transform, Load), using the current Apache Airflow. Propose new initiatives to improve performance, scalability, reliability, and overall robustness.
Collect, process, and clean data from different sources using Python & SQL.
Work side by side with the main Architects and Developers to create and ensure best practices and guidelines are being used properly by all projects.
Assess and communicate effectively the effort for required developments.
Discover new data sources to improve new and existing data pipelines. Be in charge of building and maintaining data pipelines and data models for new and existing projects.
Maintain detailed documentation of your work and changes to support data quality and governance.
Provide feedback and expert points of view as needed to help all data initiatives in the company.
Improve the quality of existing and new data processes (ETL), incorporating statistical process control, and creating alerts when anomalies are received from data sources at every step of the pipeline.
Create benchmark control of execution times for every pipeline, to control and identify potential availability issues.
Requisitos
5+ years of experience as a Data Engineer, ML Engineer, or similar.
4+ years of experience using Python object-oriented programming and scripting.
Strong experience creating data pipelines and ETL processes in modern technologies using Apache Airflow as the main workflow management tool.
4+ years of experience with the AWS data ecosystem (S3, Glue, Athena, Redshift, Lambda, EC2, RDS ...)
Experience with large-scale data and query optimization techniques using SQL.
Experience managing and monitoring data lakes systems.
Strong experience using source control management and CI/CD (GitHub actions/Gitlab pipelines). Nice to have:
Experience with containerized (Docker, Kubernetes) environments in AWS using EKS/ECS and ECR.
Knowledge and hands-on on cloud stream-processing systems.
Hand-on IAC solutions like Terraform or CloudFormation.
