Data Engineer
1 dia atrás
We are seeking a highly skilledPython Data Engineer with an AI/ML focusto join our client's growing data & analytics team in Brazil. This role is ideal for someone who loves building scalable data pipelines, operationalizing machine learning workflows, and partnering closely with data scientists to bring models into production.You will design, develop, and maintain data infrastructure that powers AI-driven insights across the organization, including data models and pipelines that run throughSnowflake . This is a fully remote position working with cross-functional product, engineering, and analytics teams.Key ResponsibilitiesBuild, optimize, and maintainETL/ELT pipelinesusing Python, modern data engineering frameworks, andSnowflakeas a central data warehouse.Architect and managedata workflows , ensuring accuracy, scalability, and reliability.Work closely with data scientists todeploy, monitor, and tune machine learning models .Developfeature engineering pipelines , preprocessing workflows, and model-serving APIs.Integrate data from various sources (APIs, databases, cloud storage, streaming platforms).ImplementMLOps best practicesincluding versioning, CI/CD for ML, and automated retraining workflows.Optimize data storage, compute usage, and performance withinSnowflakeand cloud-native tools (AWS, GCP, or Azure).Create and maintain documentation, data catalogs, and operational guides.Monitor data system performance and recommend improvements.Required Skills & Experience3–7+ years of experience as aData Engineer ,Python Engineer , or similar backend/data role.Strong proficiency inPython , including building production-grade data pipelines.Experience withSnowflake —data modeling, Snowpipe, tasks, streams, stored procedures, and performance optimization.Experience withAI/ML workflows : feature engineering, inference pipelines, or deploying models.Proficiency inSQLand relational databases (PostgreSQL, MySQL, SQL Server).Hands-on experience with at least one cloud platform ( AWS ,GCP , orAzure ).Experience using data orchestration tools likeAirflow ,Prefect , orDagster .Familiarity with MLOps tools such asMLflow, Kubeflow, SageMaker, Vertex AI , or similar.Strong understanding of data modeling, data warehousing, and distributed systems.Preferred QualificationsExperience withSpark ,Databricks , or other big-data processing tools.Experience ingesting and transforming data at scale onSnowflake , including optimization of virtual warehouses.Familiarity withKafka ,Kinesis , or other streaming platforms.Understanding of CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, etc.).Exposure to deep learning frameworks (TensorFlow, PyTorch).Experience working with Brazilian clients or LATAM distributed engineering teams.
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