Senior Backend Engineer
Senior Backend Engineer
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Job Description
Key Responsibilities:
Design and implement scalable data integration pipelines using Azure Data Factory Azure Databricks and ADLS
Develop and deploy AI/ML models using Azure Machine Learning Azure Cognitive Services and other Azure AI services
Integrate Azure AI services with existing infrastructure ensuring seamless data flow and processing
Collaborate with cross-functional teams to identify data integration and AI/ML requirements
Optimize data pipelines and AI/ML models for performance reliability and security
Troubleshoot issues and ensure high-quality data processing and AI/ML model performance
Required Skills & Experience:
Backend Development: 7 10 years of experience with Java and Spring Boot focused on building scalable microservices
API Integration: Strong understanding of REST APIs API design principles and integration patterns
Azure Data & AI Services: Strong understanding of Azure AI and data services - ADLS Azure Data Factory Azure Databricks Azure Machine Learning and Azure Cognitive Services
Data Integration: Experience with data integration tools and technologies including ETL/ELT processes
AI/ML: Knowledge of machine learning concepts including model development deployment and management
Cloud Infrastructure: Familiarity with Azure infrastructure including Azure Virtual Machines Azure Storage and Azure Networking
Database Systems: Proficient with databases like PostgreSQL MySQL or MongoDB
Nice to Have:
Azure Certifications: Relevant Azure certifications such as Azure Data Engineer or Azure AI Engineer
Cloud Architecture: Experience with designing and implementing cloud-based architectures
DevOps: Familiarity with DevOps practices including CI/CD pipelines and infrastructure as code
Security: Knowledge of security best practices including data encryption access control and threat protection
Backend Development: 7 10 years of experience with Java and Spring Boot, focused on building scalable microservices API Integration: Strong understanding of REST APIs, API design principles, and integration patterns Azure Data & AI Services: Strong understanding of Azure AI and data services - ADLS, Azure Data Factory, Azure Databricks, Azure Machine Learning, and Azure Cognitive Services Data Integration: Experience with data integration tools and technologies, including ETL/ELT processes AI/ML: Knowledge of machine learning concepts, including model development, deployment, and management Cloud Infrastructure: Familiarity with Azure infrastructure, including Azure Virtual Machines, Azure Storage, and Azure Networking Database Systems: Proficient with databases like PostgreSQL, MySQL, or MongoDB
Education
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Employment Type
Full Time
