IntegrationAnalyst

- Take full ownership and management of the end-to-end Requirements Engineering process. - Perform detailed analysis of source system data models, structures, and metadata. - Support source-to-target data mapping between applications, APIs, and events. - Document canonical models, semantic mappings, and reusable integration patterns. - Assess the technical feasibility of integration use cases. - Evaluate optimal integration patterns (API, events…). - Support architects in defining the target solution design. - Produce functional and technical specifications for integration and data flows. - Define interface contracts, mapping rules, data quality rules, error-handling rules, and validation checks. - Maintain clear and accurate documentation across all integration projects. - Work closely with Data & AI Integration Architects to ensure alignment with enterprise architecture. - Partner with Integration Engineers and Application Owners to implement data flows efficiently. - Support Data and AI Platform teams in designing ingestion strategies and metadata standards. - Develop detailed test scenarios for interface and data validation. - Support engineers in integration testing, regression testing, and data quality testing. - Validate end-to-end data flows post-implementation. - Contribute to continuous improvement of integration standards, templates, and best practices. - Support governance processes for metadata, lineage, and API/interface versioning. ## Qualifications Required - Higher education in Computer Science, Information Systems, or related technical field. - 3–5 years of experience in system integration, data analysis, or API-based data flows. - Deep understanding of data modeling, data quality, metadata, and semantics. - Ability to read and understand API specifications (OpenAPI…). - Experience with integration technologies (e.g., MuleSoft, Boomi, API gateways…). - Familiarity with cloud platforms. - Experience working in agile environments. - Excellent communi