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Key Responsibilities We are seeking a skilled Python Data Engineer with AI/ML focus to join our data & analytics team. 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. 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 including APIs, databases, cloud storage and 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. Required Skills & Qualifications 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. Hands-on experience with at least one cloud platform. Experience using data orchestration tools like Airflow, Prefect or Dagster. Familiarity with MLOps tools such as MLflow, Kubeflow, SageMaker or Vertex AI.
