Key Responsibilities
Develop and maintain data pipelines in Azure Data Factory (ADF) for data extraction and integration
Extract data from REST APIs (e.g., Kinaxis) using OAuth/token-based authentication
Retrieve and manage credentials securely using Azure Key Vault
Use REST Linked Services and Web Activities in ADF for API communication
Perform data transformation and validation within ADF pipelines
Write and optimize SQL queries, stored procedures, and views using SSMS
Support data loading and integration processes between source and target systems
Build and maintain basic data models for reporting and downstream consumption
Monitor pipeline runs and troubleshoots failures/issues
Ensure proper handling of dynamic content, parameters, and variables in ADF
Integrate enterprise applications through APIs, event-driven architecture, and cloud workflows.
Implement secure, highly available, and performant cloud solutions following Azure best practices.
Collaborate with cross-functional teams to deliver end-to-end data and integration solutions.
Strong Python development experience, preferably in backend or integration-heavy systems.
Hands-on experience with Azure Functions or other serverless cloud platforms.
Experience with unit testing frameworks such as pytest.
Ability to work with existing codebases that combine modular and object-oriented patterns.
Technical Skills
Mandatory Skills (Must have)
Azure Data Factory (ADF)
API integration using Web Activity (GET/POST)
Handling JSON responses in pipelines
Stored procedures and joins
Data extraction and transformation
Basic data modeling concepts
Work with Azure Functions when integrated with ADF pipelines
Trigger or consume Azure Functions from ADF when needed
Build event-driven architectures using Azure Function Triggers (HTTP, Timer, Blob, Queue, Service Bus).
Develop reusable functions for data validation, enrichment, transformation, and business rule execution.
Develop functions for preparing payload in xml
Design and implement workflow automation solutions using Azure Logic Apps.
Build integrations between Azure services, third-party SaaS applications, REST APIs, and enterprise systems.
Configure connectors, triggers, approvals, notifications, and workflow orchestration.
Develop error handling, retry mechanisms, and alerting workflows.
Automate business processes and data movement across cloud and on-premises systems.
Design and develop RESTful APIs using FastAPI framework.
Build high-performance, scalable microservices for data access and integration.
Implement authentication and authorization mechanisms (OAuth2, JWT, API Keys).
Develop API endpoints for real-time data ingestion and retrieval.
Azure
Azure Data Factory (ADF)
Azure App Service
Azure Key Vault (secret management)
REST Linked Service configuration
Managed Identity access
Data Integration
API integration using Web Activity (GET/POST)
OAuth/token-based authentication flows
Handling JSON responses in pipelines
Pipeline debugging and monitoring
Database & SQL
SQL Server (SSMS)
Query writing and optimization
Stored procedures and joins
Data extraction and transformation
Data Modeling
Basic data modeling concepts
Fact and dimension structure understanding
Support for reporting datasets
Azure Functions
Work with Azure Functions when integrated with ADF pipelines
Use functions for supporting API calls or preprocessing logic
Handle small transformations or utilities when required
Trigger or consume Azure Functions from ADF when needed
Build event-driven architectures using Azure Function Triggers (HTTP, Timer, Blob, Queue, Service Bus).
Develop reusable functions for data validation, enrichment, transformation, and business rule execution.
Develop functions for preparing payload in xml
Monitor and troubleshoot Azure Function execution using Application Insights and Azure Monitor.
Knowledge of XML, ZIP-based payload handling, API integrations, and asynchronous orchestration.
Azure Logic Apps
Design and implement workflow automation solutions using Azure Logic Apps.
Build integrations between Azure services, third-party SaaS applications, REST APIs, and enterprise systems.
Configure connectors, triggers, approvals, notifications, and workflow orchestration.
Develop error handling, retry mechanisms, and alerting workflows.
Automate business processes and data movement across cloud and on-premises systems.
FastAPI
Design and develop RESTful APIs using FastAPI framework.
Build high-performance, scalable microservices for data access and integration.
Implement authentication and authorization mechanisms (OAuth2, JWT, API Keys).
Develop API endpoints for real-time data ingestion and retrieval.
Create OpenAPI/Swagger documentation for developed services.
Deploy and manage FastAPI applications on Azure App Services, Azure Functions, Kubernetes, or Container Apps.
Soft Skills
Strong problem-solving skills
Attention to data accuracy and quality
Ability to work with both technical and business teams
Responsibilities
Key Responsibilities
Develop and maintain data pipelines in Azure Data Factory (ADF) for data extraction and integration
Extract data from REST APIs (e.g., Kinaxis) using OAuth/token-based authentication
Retrieve and manage credentials securely using Azure Key Vault
Use REST Linked Services and Web Activities in ADF for API communication
Perform data transformation and validation within ADF pipelines
Write and optimize SQL queries, stored procedures, and views using SSMS
Support data loading and integration processes between source and target systems
Build and maintain basic data models for reporting and downstream consumption
Monitor pipeline runs and troubleshoots failures/issues
Ensure proper handling of dynamic content, parameters, and variables in ADF
Integrate enterprise applications through APIs, event-driven architecture, and cloud workflows.
Implement secure, highly available, and performant cloud solutions following Azure best practices.
Collaborate with cross-functional teams to deliver end-to-end data and integration solutions.
Strong Python development experience, preferably in backend or integration-heavy systems.
Hands-on experience with Azure Functions or other serverless cloud platforms.
Experience with unit testing frameworks such as pytest.
Ability to work with existing codebases that combine modular and object-oriented patterns.
Technical Skills
Mandatory Skills (Must have)
Azure Data Factory (ADF)
API integration using Web Activity (GET/POST)
Handling JSON responses in pipelines
Stored procedures and joins
Data extraction and transformation
Basic data modeling concepts
Work with Azure Functions when integrated with ADF pipelines
Trigger or consume Azure Functions from ADF when needed
Build event-driven architectures using Azure Function Triggers (HTTP, Timer, Blob, Queue, Service Bus).
Develop reusable functions for data validation, enrichment, transformation, and business rule execution.
Develop functions for preparing payload in xml
Design and implement workflow automation solutions using Azure Logic Apps.
Build integrations between Azure services, third-party SaaS applications, REST APIs, and enterprise systems.
Configure connectors, triggers, approvals, notifications, and workflow orchestration.
Develop error handling, retry mechanisms, and alerting workflows.
Automate business processes and data movement across cloud and on-premises systems.
Design and develop RESTful APIs using FastAPI framework.
Build high-performance, scalable microservices for data access and integration.
Implement authentication and authorization mechanisms (OAuth2, JWT, API Keys).
Develop API endpoints for real-time data ingestion and retrieval.
Azure
Azure Data Factory (ADF)
Azure App Service
Azure Key Vault (secret management)
REST Linked Service configuration
Managed Identity access
Data Integration
API integration using Web Activity (GET/POST)
OAuth/token-based authentication flows
Handling JSON responses in pipelines
Pipeline debugging and monitoring
Database & SQL
SQL Server (SSMS)
Query writing and optimization
Stored procedures and joins
Data extraction and transformation
Data Modeling
Basic data modeling concepts
Fact and dimension structure understanding
Support for reporting datasets
Azure Functions
Work with Azure Functions when integrated with ADF pipelines
Use functions for supporting API calls or preprocessing logic
Handle small transformations or utilities when required
Trigger or consume Azure Functions from ADF when needed
Build event-driven architectures using Azure Function Triggers (HTTP, Timer, Blob, Queue, Service Bus).
Develop reusable functions for data validation, enrichment, transformation, and business rule execution.
Develop functions for preparing payload in xml
Monitor and troubleshoot Azure Function execution using Application Insights and Azure Monitor.
Knowledge of XML, ZIP-based payload handling, API integrations, and asynchronous orchestration.
Azure Logic Apps
Design and implement workflow automation solutions using Azure Logic Apps.
Build integrations between Azure services, third-party SaaS applications, REST APIs, and enterprise systems.
Configure connectors, triggers, approvals, notifications, and workflow orchestration.
Develop error handling, retry mechanisms, and alerting workflows.
Automate business processes and data movement across cloud and on-premises systems.
FastAPI
Design and develop RESTful APIs using FastAPI framework.
Build high-performance, scalable microservices for data access and integration.
Implement authentication and authorization mechanisms (OAuth2, JWT, API Keys).
Develop API endpoints for real-time data ingestion and retrieval.
Create OpenAPI/Swagger documentation for developed services.
Deploy and manage FastAPI applications on Azure App Services, Azure Functions, Kubernetes, or Container Apps.
Soft Skills
Strong problem-solving skills
Attention to data accuracy and quality
Ability to work with both technical and business teams
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
Job Description - Azure AI/M365 Copilot Search Architect
**Key Responsibilities**
- Design and implement enterprise GenAI search architectures leveraging Azure AI Search and Microsoft 365 Copilot search to deliver reliable, scalable, and intelligent discovery experiences across the organization.
- Architect retrieval-augmented generation (RAG) patterns and semantic search solutions, selecting appropriate vector search, hybrid ranking, and grounding strategies for enterprise knowledge bases.
- Analyze business requirements from diverse stakeholder groups and translate them into detailed search solution designs that balance relevance, latency, security, and cost.
- Configure and optimize indexing pipelines for structured and unstructured data, ensuring consistent ingestion, enrichment, skillset application, and normalization across multiple content repositories.
- Develop search relevance strategies including semantic ranking, vector embeddings, scoring profiles, synonym management, and domain-specific tuning to improve precision and recall for business-critical queries.
- Configure Microsoft 365 Copilot search connectors, semantic index integration, and Graph-based retrieval to surface organizational knowledge within Copilot experiences.
- Collaborate with application engineering teams to integrate search and GenAI capabilities into web portals, internal tools, and customer-facing applications using appropriate SDKs and APIs.
- Define and implement security and access models, ensuring search results respect data access policies, sensitivity labels, regulatory constraints, and privacy requirements.
- Lead client-facing architecture and consulting engagements, presenting solution designs, conducting technical workshops, and advising stakeholders on GenAI search strategy and roadmap.
- Monitor search system health by tracking relevance metrics, query latency, index freshness, and grounding quality, and recommend remediation to maintain high availability.
- Conduct capacity planning and performance testing for search and GenAI workloads, predicting growth patterns and optimizing resource utilization across cloud environments.
- Create detailed technical documentation for architectures, configurations, and runbooks, enabling operations teams to support and evolve search platforms efficiently.
- Provide guidance on migration strategies from legacy search platforms to Azure AI Search and Copilot-based solutions, minimizing disruption and ensuring continuity of critical services.
- Mentor junior engineers and architects on GenAI search technologies, design patterns, and best practices, fostering a culture of technical excellence and knowledge sharing.
**Required Skills**
- Hands-on expertise with Azure AI Search (index design, skillsets, semantic and vector search, scoring profiles).
- Hands-on experience with Microsoft 365 Copilot search, Graph connectors, and semantic index integration.
- Proven experience designing GenAI search solutions, including RAG architectures and embedding-based retrieval.
- Strong background in search architecture and solution design for enterprise environments.
- Demonstrated client-facing architecture and consulting engagement experience.
The Key Skills are Azure AI Search, Microsoft 365 Copilot Search
along with GenAI search solutions, Search Architecture , Solution Design, Client-facing architecture, and consulting engagements.
Tech Filter :
Skill/ Position title Sub skills and details Requirement Level of hire Location
Azure AI/M365 Copilot Search Architect Total exp 5-10+ Years M PAN India
Responsibilities
Job Description - Azure AI/M365 Copilot Search Architect
**Key Responsibilities**
- Design and implement enterprise GenAI search architectures leveraging Azure AI Search and Microsoft 365 Copilot search to deliver reliable, scalable, and intelligent discovery experiences across the organization.
- Architect retrieval-augmented generation (RAG) patterns and semantic search solutions, selecting appropriate vector search, hybrid ranking, and grounding strategies for enterprise knowledge bases.
- Analyze business requirements from diverse stakeholder groups and translate them into detailed search solution designs that balance relevance, latency, security, and cost.
- Configure and optimize indexing pipelines for structured and unstructured data, ensuring consistent ingestion, enrichment, skillset application, and normalization across multiple content repositories.
- Develop search relevance strategies including semantic ranking, vector embeddings, scoring profiles, synonym management, and domain-specific tuning to improve precision and recall for business-critical queries.
- Configure Microsoft 365 Copilot search connectors, semantic index integration, and Graph-based retrieval to surface organizational knowledge within Copilot experiences.
- Collaborate with application engineering teams to integrate search and GenAI capabilities into web portals, internal tools, and customer-facing applications using appropriate SDKs and APIs.
- Define and implement security and access models, ensuring search results respect data access policies, sensitivity labels, regulatory constraints, and privacy requirements.
- Lead client-facing architecture and consulting engagements, presenting solution designs, conducting technical workshops, and advising stakeholders on GenAI search strategy and roadmap.
- Monitor search system health by tracking relevance metrics, query latency, index freshness, and grounding quality, and recommend remediation to maintain high availability.
- Conduct capacity planning and performance testing for search and GenAI workloads, predicting growth patterns and optimizing resource utilization across cloud environments.
- Create detailed technical documentation for architectures, configurations, and runbooks, enabling operations teams to support and evolve search platforms efficiently.
- Provide guidance on migration strategies from legacy search platforms to Azure AI Search and Copilot-based solutions, minimizing disruption and ensuring continuity of critical services.
- Mentor junior engineers and architects on GenAI search technologies, design patterns, and best practices, fostering a culture of technical excellence and knowledge sharing.
**Required Skills**
- Hands-on expertise with Azure AI Search (index design, skillsets, semantic and vector search, scoring profiles).
- Hands-on experience with Microsoft 365 Copilot search, Graph connectors, and semantic index integration.
- Proven experience designing GenAI search solutions, including RAG architectures and embedding-based retrieval.
- Strong background in search architecture and solution design for enterprise environments.
- Demonstrated client-facing architecture and consulting engagement experience.
The Key Skills are Azure AI Search, Microsoft 365 Copilot Search
along with GenAI search solutions, Search Architecture , Solution Design, Client-facing architecture, and consulting engagements.
Tech Filter :
Skill/ Position title Sub skills and details Requirement Level of hire Location
Azure AI/M365 Copilot Search Architect Total exp 5-10+ Years M PAN India
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
