Role Summary
A highly experienced, hands-on Senior Integration Developer responsible for designing and delivering complex, enterprise-grade integration solutions. Drives advanced development, owns Low-Level Design (LLDs), and ensures high-quality, CI/CD-driven delivery using Azure Integration Services, while mentoring teams and contributing to architecture alignment.
Key Responsibilities
Core Development (Primary Focus)
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Lead the development of complex, large-scale integration solutions using Azure Integration Services (Logic Apps, Azure Functions, Data Factory, Service Bus, Event Grid).
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Build high-performance, scalable, and production-ready solutions, handling complex enterprise integration scenarios.
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Develop reusable frameworks, advanced integration patterns, and shared components to accelerate delivery across programs.
API Development & APIM Governance
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Design and implement enterprise-grade APIs using Azure API Management (APIM).
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Configure advanced APIM policies including security, transformation, throttling, and routing.
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Ensure APIs meet performance, security, and governance standards.
Low-Level Design & Technical Ownership
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Own and drive Low-Level Design (LLDs) for modules and critical components.
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Translate business and architectural requirements into scalable, well-structured technical designs.
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Ensure strict adherence to architecture standards, design principles, and best practices.
Azure DevOps & CI/CD (Key Responsibility)
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Design, implement, and optimize CI/CD pipelines using Azure DevOps / GitHub Actions.
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Drive end-to-end automation of build, deployment, and release processes using Infrastructure as Code (IaC).
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Ensure consistent, reliable, and high-quality releases across environments.
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Improve deployment efficiency, rollback strategies, and release governance.
Testing, Debugging & Production Support
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Lead unit testing, integration testing, and validation strategies.
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Handle complex debugging and root cause analysis across APIs, events, and workflows.
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Provide strong support for critical production issues and performance bottlenecks.
Monitoring, Reliability & Performance
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Implement and enhance observability frameworks using Azure Monitor and Application Insights.
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Ensure solutions meet SLAs for reliability, scalability, and performance.
AI & Copilot-Enabled Development
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Actively leverage GitHub Copilot / M365 Copilot for:
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Code acceleration and optimization
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LLD and API documentation generation
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Debugging and performance insights
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Apply AI-assisted engineering practices to improve productivity and delivery quality.
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Contribute to adoption of AI-driven development practices within the team.
Technical Leadership & Mentoring
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Provide hands-on technical leadership, guiding developers on design, coding, and best practices.
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Conduct code reviews, design reviews, and quality checks.
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Mentor engineers and junior developers, building strong technical capability across the team.
Collaboration in Complex Delivery Programs
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Work closely with Leads, Architects, QA, DevOps, and business stakeholders.
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Drive alignment between design, development, and delivery timelines.
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Actively contribute to high-velocity, agile delivery environments.
Required Skills
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Experience: 6–9 years with strong focus on hands-on integration development in complex delivery environments.
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Azure Integration: Deep expertise in Azure Integration Services (AIS).
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API Development: Advanced experience with Azure API Management (APIM).
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Programming: Strong coding expertise in C#, .NET, REST APIs, JSON, XML.
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Design Skills: Proven experience in owning LLDs and contributing to HLDs.
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Integration Patterns: Strong knowledge of event-driven, distributed, and microservices-based architectures.
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Azure CI/CD: Hands-on expertise in designing and managing CI/CD pipelines using Azure DevOps / GitHub Actions.
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Debugging & Performance: Advanced troubleshooting and optimization skills.
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AI & Copilot Skills:
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Active and effective use of GitHub Copilot / M365 Copilot
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Practical understanding of AI-assisted development workflows
Preferred Skills
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Experience with MuleSoft (architecture, migrations, or coexistence).
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Exposure to AI/ML integration use cases and intelligent automation.
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Knowledge of enterprise security, API governance, and compliance frameworks.
