Senior Data Architect

2 semanas atrás

Brasil beBeeDataEngineer Tempo inteiro

We are seeking a highly skilled data professional to join our client's growing data and 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 through Snowflake . This is a fully remote position working with cross-functional product, engineering, and analytics teams. Key Responsibilities: Build, optimize, and maintain ETL/ELT pipelines using Python, modern data engineering frameworks, and Snowflake as a central data warehouse. Architect and manage data workflows, ensuring accuracy, scalability, and reliability. Work closely with data scientists to deploy, monitor, and tune machine learning models. Develop feature engineering pipelines, preprocessing workflows, and model-serving APIs. Integrate data from various sources (APIs, databases, cloud storage, streaming platforms). Implement MLOps best practices including versioning, CI/CD for ML, and automated retraining workflows. Optimize data storage, compute usage, and performance within Snowflake and 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 & Experience: 3–7+ years of experience as a Data Engineer, Python Engineer, or similar backend/data role. Strong proficiency in Python, including building production-grade data pipelines. Experience with Snowflake—data modeling, Snowpipe, tasks, streams, stored procedures, and performance optimization. Experience with AI/ML workflows: feature engineering, inference pipelines, or deploying models. Proficiency in SQL and relational databases (PostgreSQL, MySQL, SQL Server). Hands-on experience with at least one cloud platform (AWS, GCP, or Azure). Experience using data orchestration tools like Airflow, Prefect, or Dagster. Familiarity with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI , or similar. Strong understanding of data modeling, data warehousing, and distributed systems. Benefits: Opportunity to work on complex data projects. Collaborative environment with cross-functional teams. Flexible remote work arrangements. Others: This role requires a strong passion for data engineering, machine learning, and collaboration. We are looking for a self-motivated individual who can work independently and as part of a team to deliver high-quality results.

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