Data Integration Engineer

Client is specifically looking for an Integration Developer with experience in IBM Webmethods (also known as IBM API Connect).

Data Integration Engineer

Client is seeking a talented individual to design, develop, test, and support enterprise data integration solutions that enable reliable data movement, transformation, and delivery across on-premises and cloud-based platforms. This role contributes to the development of scalable ETL processes, APIs, event-driven integrations, and automated data workflows supporting critical business applications, data platforms, operational reporting, analytics, and Artificial Intelligence (AI) initiatives.

The Data Integration Engineer will collaborate with business stakeholders, Data Engineers, Application Development teams, Solution Architects, vendors, and operations teams to analyze data requirements, design integration solutions, and ensure data quality across the enterprise. This position provides exposure to modern cloud technologies, AI-assisted development tools, enterprise integration platforms, and emerging data engineering practices.

Summary

Client is actively transforming its technology landscape through cloud modernization, intelligent automation, advanced analytics, and AI-driven solutions. In this role, you will work with modern integration platforms, cloud technologies, databases, APIs, and automation tools while gaining hands-on experience designing data solutions that power business processes across the enterprise. You will have opportunities to grow your skills in cloud data engineering, API development, event-driven architecture, AI-assisted development, and modern software delivery practices while contributing to high-impact strategic initiatives.

Duties

1. Collaborates with business users, data owners, and technical teams to gather, analyze, and document data integration requirements.
2. Performs data analysis, profiling, validation, and source-to-target mapping activities.
3. Designs, develops, tests, and supports ETL and ELT processes using enterprise integration and data management technologies.
4. Develops data transformation, enrichment, aggregation, and validation logic supporting operational and analytical workloads.
5. Assists in the development and maintenance of APIs, file-based integrations, database integrations, and event-driven data processes.
6. Creates and maintains Structured Query Language (SQL) code, stored procedures, views, functions, and data-processing components.
7. Supports integration solutions utilizing cloud-based services and data platforms including AWS services such as S3, Aurora, RDS, DynamoDB, EC2, and related technologies.
8. Participates in the design, development, and support of real-time, batch, and near real-time integration solutions.
9. Assists with implementation of monitoring, alerting, logging, and operational support capabilities for integration services and data pipelines.
10. Troubleshoots data quality issues, integration failures, performance bottlenecks, and production incidents.
11. Supports testing activities including unit testing, system integration testing, user acceptance testing, and defect resolution.
12. Participates in code reviews, architecture discussions, technical design sessions, and continuous improvement initiatives.
13. Utilizes AI-assisted development and productivity tools to improve solution quality, documentation, testing, and development efficiency.
14. Maintains technical documentation including mappings, process flows, operational procedures, knowledge articles, and support artifacts.
15. Supports DevOps and CI/CD practices including source control, automated deployments, and release management activities.
16. Assists with implementation of data governance, security, privacy, and compliance requirements.
17. Develops and maintains dashboards, reports, monitoring solutions, and operational metrics related to integration services and data quality.
18. Researches emerging technologies, cloud services, AI capabilities, and industry best practices to support continuous innovation.
19. Collaborates effectively with internal teams, external vendors, and business partners to deliver integration solutions.
20. Performs all other duties as assigned.
    
    

Qualifications

1. Bachelor's degree in Computer Science, Information Systems, Information Technology, Software Engineering, Mathematics, Engineering, or related technical discipline; equivalent experience may be considered.
2. One (1) or more years of experience in Data Integration Engineering, ETL Development, Data Engineering, Application Integration, or related disciplines.
3. Experience working with ETL, ELT, integration, or data movement technologies such as Information Builders, IBM webMethods, Informatica, Talend, Microsoft, or equivalent platforms.
4. Working knowledge of relational database systems including Microsoft SQL Server, PostgreSQL, Oracle, MySQL, DB2, or similar technologies.
5. Demonstrated proficiency with SQL for querying, transforming, validating, and troubleshooting data.
6. Knowledge of common data formats and integration standards including JSON, XML, CSV, REST APIs, and web services.
7. Understanding of data quality, data validation, data cleansing, and data governance concepts.
8. Familiarity with cloud computing concepts and services, preferably AWS, Azure, or similar cloud platforms.
9. Exposure to cloud data services such as S3, RDS, Aurora, DynamoDB, Redshift, or equivalent technologies is preferred.
10. Exposure to APIs, middleware platforms, enterprise integration technologies, message queues, or event-driven architectures is preferred.
11. Experience utilizing source control tools such as Git, GitHub, Azure DevOps, or equivalent platforms is preferred.
12. Understanding of Agile methodologies, the Software Development Life Cycle (SDLC), and DevOps practices.
13. Familiarity with scripting or programming languages such as Python, Java, PowerShell, or JavaScript is preferred.
14. Familiarity with AI-assisted development tools, intelligent automation platforms, generative AI technologies, or machine learning concepts is preferred.
15. Strong analytical, organizational, troubleshooting, and problem-solving skills.
16. Strong verbal and written communication skills with the ability to communicate technical concepts to both technical and non-technical audiences.
17. Ability to work independently while collaborating effectively within cross-functional teams.
18. Financial services, insurance, lending, or other regulated industry experience is preferred.
19. Cloud, Data Engineering, AI, Agile, or related technical certifications are preferred.