Job Title Senior Azure Data Engineer AIML Fraud Analytics
Argyle Infotech
Senior Azure Data Engineer – AI/ML & Fraud Analytics Location: Redmond, WA (Hybrid) Employment Type: Contract (12 Months) Experience: 10+ Years Work Authorization: Visa Independent Candidates Only Interview Process: Virtual Job Summary: We are seeking a highly experienced Senior Azure Data Engineer with strong expertise in Python, PySpark, Machine Learning, Deep Learning, and Azure Cloud technologies to support enterprise-scale AI and data engineering initiatives within the Fraud and Risk domain. The ideal candidate will have extensive experience in designing scalable data platforms, developing intelligent data pipelines, and operationalizing machine learning models in cloud-based production environments. The successful candidate will work closely with data scientists, ML engineers, architects, and business stakeholders to build high-performance data solutions, automate ML workflows, and enable real-time fraud detection and risk analytics using modern Azure technologies. Key Responsibilities Azure Data Engineering Machine Learning & AI MLOps & Automation Fraud & Risk Analytics Cloud Architecture Data Visualization & Reporting Leadership & Collaboration Production Support Required Qualifications: Experience: Minimum 10+ years of overall IT experience. Strong experience in Azure Data Engineering and AI/ML solutions. Proven expertise building enterprise-scale cloud-based data platforms. Hands-on experience operationalizing Machine Learning solutions in production. Technical Skills: Programming Languages: Python, PySpark, SQL, C# (Preferred) AI & Data Science: Machine Learning, Deep Learning, Predictive Analytics, Model Deployment, Model Monitoring, Model Versioning, MLOps Azure Technologies: Microsoft Azure, Azure Machine Learning, Azure Databricks, Azure Data Factory, Azure DevOps, Azure Storage Data Engineering: ETL/ELT, Big Data Processing, Data Pipelines, Distributed Computing Reporting & Analytics: Power BI, Kusto Query Language (KQL) DevOps & Tools: Git, CI/CD, Docker, Kubernetes Methodologies: Agile, Scrum, SDLC Argyle Infotech
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