Digitalization Engineer

We are seeking a skilled Data Science Engineer to design, develop, and deploy advanced data solutions leveraging Microsoft Azure services/ AWS . The ideal candidate will have strong expertise in cloud architecture, data engineering, machine learning, and ensuring scalable and secure data pipelines and AI models for business insights. 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.