As part of our client's Technology Applications Engineering team, you will play a pivotal role in solution-oriented application integration and formatting of structured data sources for AI enablement. This role focuses on designing, implementing, and maintaining integration that connect various data sources internal and external to enterprise applications and AI systems. You will work across various projects, applying a mix of technical expertise, creativity, and problem-solving skills. You will be proactive in identifying areas for improvement, innovating new solutions, and driving projects forward. Supporting the firms needs, you will develop a good understanding of how the firm operates. You will also be an integral part of our focus on delivering the Firms vision of profitable growth and will champion our internal culture. Aware of the contribution that you can make to the plans and decisions that will deliver engaged people and outstanding client relationships around the world, you will be confident in speaking up and proactively look for ways to make a difference and implement process improvements. In return, you will have a front-row seat in a business that is changing rapidly within a team that is friendly, supportive and welcoming. Duties include the below:
-Design and implement scalable, maintainable data integration solutions that enable structured data delivery into bespoke or COTS AI and analytics platforms
-Develop and manage API-based and event-driven integrations across databases, SaaS platforms, on-premises systems, and external data providers
-Format and normalize structured data to support analytics, generative AI, and LLM-based systems
-Collaborate closely with data scientists, AI engineers, and business application teams to understand integration needs and ensure delivery of clean, timely, and usable data
-Build and document data transformation logic, integration workflows, and metadata catalogs to promote reusability and governance
-Establish delivery systems and processes that support both batch and real-time data processing
-Contribute to the development of standards, templates, and reusable components for data ingestion and transformation
-Proactively monitor and troubleshoot data flow and system integration performance issues
-Participate in full software development lifecycle (SDLC) activities, including design, development, testing, deployment, and support
-Familiar with DevOps best practices, including CI/CD pipelines, Infrastructure as Code (IaC), and automated testing
-Troubleshoot technical issues and implement bug fixes proactively
-Stay informed of the latest Microsoft and AI advancements, incorporating new technologies where applicable
-Maintain the practice of continuous improvement and education by attending seminars
-Interact with all levels of staff
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal. com. To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
-B. S. degree in Computer Science, Software Engineering or related field, or equivalent experience
-7+ years of experience in data integration, application integration, or enterprise middleware engineering roles
-4+ years of experience within the AI and Machine Learning IT Spaces
-Proven expertise in working with structured data and relational systems (SQL Server, Oracle, PostgreSQL, etc.)
Strong hands-on experience with APIs (REST, SOAP, GraphQL) and integration tools/platforms
-Familiarity with cloud-based data services (Azure, AWS, or GCP), including data lakes, storage, and streaming technologies (Kafka, Event Grid)
-Experience building ETL/ELT pipelines and working with JSON, XML, and other common data exchange formats
-Knowledge of data modeling, normalization, and schema design principles
-Understanding of data security, privacy, and compliance requirements
-Strong knowledge of DevOps methodologies, CI/CD pipelines, and Git-based workflows
-Experience integrating with AI/ML pipelines or knowledge of data preparation for large language models (LLMs)
-Familiarity with Microsoft Power Platform and SharePoint
-Exposure to knowledge graphs, vector databases, or semantic enrichment strategies
-Hands-on experience with data cataloging tools