Digitalization Engineer

Role Overview

Data Science Engineer

Key Responsibilities

• Data Engineering & Integration:
• Design and implement data pipelines using Azure Data Factory, Azure Synapse Analytics, and Azure Databricks.
• Integrate structured and unstructured data from multiple sources into Azure-based data lakes and warehouses.
• Machine Learning & AI Development:
• Build and deploy ML models using Azure Machine Learning and Python/R.
• Optimize model performance and manage lifecycle with MLOps practices.
• Cloud Architecture & Optimization:
• Architect scalable solutions using Azure Storage, Azure SQL Database, and Azure Kubernetes Service (AKS).
• Ensure cost optimization and performance tuning across Azure resources.
• Security & Compliance:
• Implement data governance, security policies, and compliance standards (GDPR, HIPAA, etc.).
• Manage role-based access and encryption for sensitive data.
• Collaboration & Documentation:
• Work closely with data scientists, analysts, and business stakeholders to deliver actionable insights.
• Document workflows, architecture diagrams, and best practices.

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
• 3+ years of experience in Azure Data Services and Cloud-based Data Engineering.
• Hands-on experience with Azure Machine Learning, Data Factory, Synapse, and Databricks , AWS
• Strong understanding of ETL processes, data modeling, and big data frameworks
• Excellent problem-solving and communication skills.