Azure Data Engineer

Company Description TechZavy Inc. is a software solutions and IT services company delivering managed IT services including custom software development, devSecOps, data migration, and application re-engineering for Agentic AI services, microservices and cloud-native architectures. TechZavy also provides infrastructure services across public, private, and hybrid cloud environments to keep clients at the leading edge of cloud, analytics, mobility, and security. Its AI and ML solutions turn complex data into actionable insights through advanced analytics and augmented business intelligence. TechZavy applies design thinking, a technology-agnostic approach, and agile DevOps practices to connect IoT systems and accelerate time-to-market for its customers. Role Description This is a full-time remote position for an Azure Data Engineer at TechZavy. Minimum Requirements · Bachelor’s degree in computer science, Information Technology, Computer Engineering, or an equivalent technical field. · Minimum 10 years of experience in SQL programming designing & developing, relational and non-relational databases in Microsoft SQL Server/ Oracle / Azure SQL · Hands-on experience building/modernizing data pipelines using Azure Data Bricks/Data Factory/Synapse/Azure Fabric. · Proficiency in schema design , data modeling , performance optimization , and integrating relational/non-relational data environments using data lake/ delta lake architecture · C ertifications in Azure Data Engineer Associate or Azure Solutions Architect Expert a plus Key Technical Competencies desired AI Application & Workflow Engineering · AI-Driven Applications: Experience designing and deploying web applications powered by OpenAI / Azure AI Services APIs, Semantic Kernel, or n8n. · AI Agents & Process Automation: Demonstrated ability to build autonomous AI workflows and intelligent agents for enterprise process automation and customer-facing interfaces. LLM Orchestration & Prompt Engineering · LLM Integration & Prompting: Understanding of LLM APIs, prompt engineering strategies, context window management, and output optimization. · Accuracy & Hallucination Mitigation: Hands-on expertise in building Retrieval-Augmented Generation (RAG) architecture to minimize model hallucinations and ensure high-reliability AI responses. Security, DevOps & System Reliability · Security & Governance: Experience implementing RBAC, network isolation, enterprise encryption, and alignment with enterprise security guidelines. · CI/CD & Monitoring: Familiarity with DevOps pipelines, automated deployment, and system monitoring/backup strategies (Azure Backup, Geo-replication). Show more Show less