Messaging & integration engineer

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 Git Hub 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 Git Hub 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 Git Hub 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, Git Hub 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.