Data Engineer

As a Data Engineer in the Advanced Analytics team, your primary focus will be on ensuring the stability, reliability, and performance of ML models in production environments. You will design, develop, and manage ETL data pipelines, deploy and scale existing machine learning models, and collaborate closely with data scientists to provide clean, well-structured data for modeling.

Requirements

• Master’s degree in computer science, software engineering, or an equally technical field
• 2+ years of previous data engineering experience with Azure-related data technologies
• Proven experience in deploying and managing AI models in production environments
• Hands-on knowledge of Azure Databricks, Azure Data Factory, Azure Data Lake Storage, Synapse Serverless/dedicated/spark pools, Python, PySpark, and MLflow
• Solid understanding of model performance metrics and evaluation techniques
• Proficiency in programming languages commonly used in ML development such as Python and R
• Experience with model deployment frameworks (e.g., TensorFlow Serving), containerization (e.g., Kubernetes, Docker), and cloud platforms (e.g., Azure)
• Familiarity with DevOps practices and tools for CI/CD pipelines (e.g., GitLab, Jenkins) in the context of deploying AI models
• Understanding of Azure infrastructure, including subscriptions, resource groups, resources, access control with role-based access control, integrations with Azure AD, and Azure security principles (user group, service principal, managed identity), password/credential/key management, and data protection
• Excellent problem-solving skills with a focus on root cause analysis and continuous improvement
• Excellent oral and written communication skills, with the ability to communicate both technical and business concepts, as well as strong presentation skills
• Adaptability and willingness to learn new things and stay on top of the new deployment and ETL updates
• Ability to lead technical presentations, demonstrations, workshops, design sessions, proofs of concept, and pilots

Benefits

• Comprehensive benefits
• Retirement programs
• Performance incentives
• Continuing Education Programs
• Other perks to support well-being
• Career growth opportunities
• Product discounts