You will be part of our Data Science team, responsible for developing, maintaining and evolving analytical solutions and machine learning models that support multiple business areas.
We operate in a collaborative environment with a strong engineering culture, a focus on data quality, and continuous improvement.
In this project, you will play a strategic role in migrating integrations, pipelines and data consumers currently running on AWS to the GCP ecosystem, ensuring operational continuity, reliability and adherence to data engineering and machine learning best practices.
Perform the migration of connections, pipelines and data consumption processes from AWS to GCP for the company's Data Science projects.
Adapt queries, integrations and data processing routines to run in the GCP environment, taking into account differences between services and SQL dialects.
Execute functional tests, consistency validations and data sign-off after migration processes.
Support the migration of analytical workloads and machine learning pipelines to equivalent services within the GCP ecosystem.
Work closely with data engineering, architecture and MLOps teams to ensure stability and efficiency of migrated solutions.
Identify and resolve issues related to performance, compatibility and governance during the cloud transition.
Document technical processes, data flows and architectural decisions related to the migration.
Contribute to standardization, automation and quality improvements in pipelines and analytical processes.
Requirements
Strong experience as a Data Scientist or Machine Learning Engineer in production environments.
Hands-on experience with cloud environments, especially AWS and GCP.
Advanced SQL skills for adapting and optimizing queries.
Experience with data manipulation and processing using Python.
Experience with data pipelines and integrations across different cloud services.
Experience with testing and validating data consistency during migration processes.
Knowledge of analytics and data services in AWS and GCP.
Ability to work autonomously on complex technical problems.
Good communication skills and ability to interact with multidisciplinary teams.