IntraEdge
1 month ago
Messaging & Integration Engineer
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Company information
- Company
- IntraEdge
- Location
- India, Telangana, Hyderabad India
- Posted
- 1 month ago
Job description
Messaging & Integration Engineer
Location: Hyderabad
Experience: 3–6 Years
Employment Type: Full-Time
Job Summary
We are seeking a skilled Messaging & Integration Engineer with experience in enterprise messaging, system integration, data processing, and event-driven architectures. The ideal candidate will have hands-on experience with Kafka, IBM MQ, REST APIs, JSON/XML, and enterprise application integration.
The candidate will be responsible for supporting and developing integration solutions across complex enterprise environments and will work with Commercial Off-the-Shelf (COTS) products such as SAS and Archer. The role requires strong troubleshooting capabilities, a willingness to learn new enterprise applications, and familiarity with modern AI-enabled development tools such as GitHub Copilot.
Key Responsibilities
Messaging & Integration
- Design, develop, configure, and support enterprise integration solutions using Kafka, MQ, and related messaging technologies.
- Work with asynchronous messaging and event-driven communication patterns.
- Understand message producers, consumers, queues, topics, partitions, offsets, acknowledgements, and message delivery mechanisms.
- Configure and troubleshoot message flows between enterprise applications.
- Monitor message processing and investigate failed, delayed, or duplicate messages.
- Ensure reliable and secure data exchange between applications and platforms.
Kafka
- Work with Kafka topics, producers, consumers, consumer groups, and partitions.
- Develop and support Kafka-based event-processing solutions.
- Troubleshoot consumer lag, message processing failures, connectivity issues, and configuration problems.
- Understand event ordering, message retention, offsets, and error-handling mechanisms.
- Support integration of enterprise applications using Kafka-based event streams.
IBM MQ / Messaging
- Work with IBM MQ or similar enterprise messaging platforms.
- Support queues, queue managers, channels, and message flows.
- Troubleshoot message delivery and connectivity issues.
- Analyze message payloads and identify data or routing problems.
- Coordinate with middleware and application teams to resolve messaging issues.
API & System Integration
- Develop, consume, configure, and support REST APIs.
- Work with API request and response structures.
- Handle JSON and XML payloads.
- Troubleshoot HTTP/API errors and integration failures.
- Understand HTTP methods, status codes, headers, authentication, and error handling.
- Perform API testing using tools such as Postman or equivalent.
- Integrate APIs with messaging platforms, databases, and enterprise applications.
- Analyze end-to-end integration flows across multiple systems.
Data Processing
- Understand data processing and transformation requirements across enterprise applications.
- Analyze source and target data to identify discrepancies.
- Support data mapping, transformation, validation, and routing.
- Troubleshoot data processing failures and integration issues.
- Ensure accurate and reliable movement of data between upstream and downstream systems.
- Work with structured formats such as JSON and XML.
Event-Driven Architecture
- Understand fundamental concepts of event-driven architecture and distributed systems.
- Design and support asynchronous, loosely coupled application integrations.
- Understand event producers, consumers, event streams, and message-based communication.
- Participate in designing scalable and reliable integration patterns.
- Identify appropriate messaging and integration approaches based on application requirements.
Enterprise Application & COTS Product Support
- Learn and support enterprise applications and Commercial Off-the-Shelf (COTS) products.
- Gain functional and technical understanding of products such as:
- SAS
- Archer
- Other enterprise risk, analytics, compliance, or business applications
- Understand application dependencies, integration points, interfaces, and data flows.
- Support configuration, troubleshooting, testing, and integration activities.
- Work closely with product vendors and internal application teams when required.
- Adapt quickly to new technologies and enterprise platforms.
Application Support & Troubleshooting
- Provide technical support for enterprise applications and integration components.
- Monitor application and integration health.
- Analyze application logs, messaging logs, API responses, and error messages.
- Perform root cause analysis for production issues.
- Troubleshoot connectivity, configuration, data, messaging, and API-related problems.
- Participate in incident, problem, and change management processes.
- Support production deployments and post-deployment validation.
- Ensure issues are resolved within defined SLAs.
AI-Enabled Development
- Use AI-enabled development tools such as GitHub Copilot to improve productivity.
- Leverage AI-assisted tools for:
- Code development
- Code optimization
- Debugging
- Documentation
- Test case generation
- Troubleshooting
- Follow organizational security and governance guidelines when using AI-assisted development tools.
- Stay updated with emerging AI-enabled software development practices.
Development & Automation
- Develop scripts or application components to automate repetitive integration and operational activities.
- Exposure to Java, Python, or other programming/scripting languages is preferred.
- Use Git or other source-control systems for managing application and integration code.
- Participate in code reviews and follow enterprise coding standards.
- Support automation of testing, deployment, monitoring, and operational processes.
Testing & Deployment
- Develop and execute unit and integration test cases for messaging and API-based integrations.
- Validate message flows and API responses.
- Perform end-to-end integration testing across upstream and downstream systems.
- Support deployment activities across development, QA, UAT, and production environments.
- Troubleshoot deployment and configuration issues.
- Validate integrations following application releases or infrastructure changes.
Required Skills & Qualifications
Must-Have Skills
- 3–6 years of relevant IT experience in integration, middleware, application development, or enterprise application support.
- Hands-on experience with Kafka and/or MQ.
- Strong understanding of messaging and integration technologies.
- Understanding of data processing and system integration.
- Good knowledge of event-driven architectures.
- Experience working with REST APIs.
- Strong understanding of JSON and XML.
- Good troubleshooting and analytical skills.
- Familiarity with GitHub Copilot or similar AI-enabled development tools.
- Ability and willingness to learn and support enterprise applications and COTS products.
Good-to-Have Skills
- Experience with SAS or Archer.
- Experience with IBM MQ.
- Experience with Kafka administration or development.
- Knowledge of Java or Python.
- Experience with API gateways or integration platforms.
- Knowledge of cloud platforms such as AWS, Azure, or GCP.
- Experience with Docker/Kubernetes.
- Exposure to CI/CD tools such as Jenkins, GitHub Actions, or similar.
- Experience with application monitoring and observability tools.
- Experience working in Banking, Financial Services, Insurance, or other regulated industries.
Candidate Profile
The ideal candidate should be:
- Strong in enterprise application integration and messaging concepts.
- Comfortable working with Kafka, MQ, REST, JSON/XML, and event-driven systems.
- Capable of troubleshooting complex integration and production issues.
- Comfortable learning unfamiliar enterprise applications and COTS products.
- Able to understand application architecture and end-to-end data flows.
- Interested in adopting modern AI-assisted development practices.
- A strong communicator who can collaborate effectively with developers, architects, infrastructure teams, business users, and vendors.
- Comfortable working in a fast-paced enterprise environment with multiple applications and dependencies.
Required skills
- kafka
- docker
- sas
- debugging
- communication
- compliance
- documentation
- java
- security
- application support
- databases
- governance
- financial services
- python
- aws
- kubernetes
- troubleshooting
- automation
- insurance
- git
- collaboration
- jenkins
- github actions
- testing
- gcp
- azure
- code reviews
- architects
- rest apis
- engineer
- change management
- analytics
- cloud platforms
- json
- postman
- interfaces
- observability tools
- messaging
- root cause analysis
- fast-paced environment
- incident management
- integration
- scripting languages
- banking
- xml
- configuration
- distributed systems
- headers
- system integration
- data processing
- problem management
- api testing
- event-driven architecture
- application development
- authentication
- slas
- event-driven architectures
- testing automation
- developers
- production environment
- ibm mq
- data validation
- channels
- vendors
- middleware
- data mapping
- data transformation
- cots
- connectivity issues
- regulated industries
- integration points
- data exchange
- business users
- programming languages
- coding standards
- application architecture
- scripts
- deployment automation
- ai-assisted tools
- code optimization
- queues
- github copilot
- ci/cd tools
- messaging technologies
- hyderabad
- business applications
- enterprise application integration
- integration platforms
- message processing
- message flows
- it experience
- messaging platforms
- partitions
- consumers
- data flows
- application teams
- api gateways
- error-handling
- error messages
- enterprise environment
- operational activities
- unit test cases
- archer
- http methods
- asynchronous messaging
- software development practices
- application monitoring
- event streams
- integration components
- code development
- topics
- infrastructure teams
- application health
- end-to-end integration testing
- offsets
- end-to-end integration
- production issues
- production deployments
- infrastructure changes
- development environment
- application logs
- status codes
- acknowledgements
- product vendors
- enterprise risk
- test case generation
- data routing
- commercial off-the-shelf (cots)
- ai-enabled development tools
- enterprise application support
- message producers
- message delivery
- consumer lag
- configuration problems
- event ordering
- message retention
- queue managers
- message payloads
- routing problems
- api request
- response structures
- upstream systems
- downstream systems
- loosely coupled integrations
- event producers
- message-based communication
- scalable integration patterns
- application dependencies
- messaging logs
- api responses
- post-deployment validation
- source-control systems
- monitoring automation
- operational process automation
- integration test cases
- message validation
- api response validation
- qa environment
- uat environment
- deployment issues
- configuration issues
- application releases
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