Data / Integration Engineer

• Design, develop, and maintain scalable document ingestion and processing pipelines to support enterprise knowledge management and AI-powered applications. • Build and optimize multi-stage data workflows for extracting, transforming, enriching, and indexing content from diverse document formats including PDF, PPTX, DOCX, CSV, and image-based sources. • Implement advanced document processing capabilities, including metadata extraction, content chunking, classification, summarization, and information retrieval workflows. • Manage vector database indexing strategies and search optimization to ensure high-quality retrieval performance and relevance. • Develop and maintain MCP-compatible tool servers that securely expose enterprise databases, APIs, cloud platforms, and external services to AI agents. • Design and implement event-driven architectures leveraging messaging and integration services to enable scalable and responsive data processing solutions. • Create and deploy data analysis, document intelligence, and knowledge retrieval agents using reusable development templates and platform tooling. • Collaborate with cross-functional teams to deliver reliable, scalable, and innovative data engineering and AI-driven solutions. Basic Qualifications: • Bachelor's degree in Computer Science, Data Engineering, Information Technology, Artificial Intelligence, or equivalent combination of education and experience. • Typically, 3+ years of professional experience in Python development and data pipeline engineering. • Hands-on experience designing and maintaining ETL/ELT workflows using orchestration platforms such as Dagster, Airflow, or equivalent technologies. • Strong proficiency with document processing frameworks and libraries for extracting and transforming content from structured and unstructured data sources. • Experience working with vector databases, embedding models, semantic search technologies, and retrieval optimization techniques. • Familiarity with Azure data and AI services, including Azure AI Search, Blob Storage, Event Hub, Document Intelligence, or comparable cloud-native platforms. • Proven experience developing containerized applications and pipeline components using Docker and modern deployment practices. • Strong understanding of REST API design, integration patterns, and service-oriented architectures. • Experience building scalable ingestion, indexing, and retrieval systems for data-intensive applications. Other Qualifications: • Experience with Retrieval-Augmented Generation (RAG) architectures and enterprise knowledge management platforms is a plus. • Familiarity with event-driven system design and distributed data processing patterns is preferred. • Knowledge of AI agent ecosystems, MCP integrations, and modern data-to-agent architectures is highly desirable. • Strong analytical, troubleshooting, and problem-solving skills. • Excellent communication and collaboration abilities across technical and business stakeholders. • Relevant certifications in Azure, Data Engineering, Artificial Intelligence, or Cloud Technologies are a plus.

Basic Qualifications: • Bachelor's degree in Computer Science, Data Engineering, Information Technology, Artificial Intelligence, or equivalent combination of education and experience. • Typically, 3+ years of professional experience in Python development and data pipeline engineering. • Hands-on experience designing and maintaining ETL/ELT workflows using orchestration platforms such as Dagster, Airflow, or equivalent technologies. • Strong proficiency with document processing frameworks and libraries for extracting and transforming content from structured and unstructured data sources. • Experience working with vector databases, embedding models, semantic search technologies, and retrieval optimization techniques. • Familiarity with Azure data and AI services, including Azure AI Search, Blob Storage, Event Hub, Document Intelligence, or comparable cloud-native platforms. • Proven experience developing containerized applications and pipeline components using Docker and modern deployment practices. • Strong understanding of REST API design, integration patterns, and service-oriented architectures. • Experience building scalable ingestion, indexing, and retrieval systems for data-intensive applications. Other Qualifications: • Experience with Retrieval-Augmented Generation (RAG) architectures and enterprise knowledge management platforms is a plus. • Familiarity with event-driven system design and distributed data processing patterns is preferred. • Knowledge of AI agent ecosystems, MCP integrations, and modern data-to-agent architectures is highly desirable. • Strong analytical, troubleshooting, and problem-solving skills. • Excellent communication and collaboration abilities across technical and business stakeholders. • Relevant certifications in Azure, Data Engineering, Artificial Intelligence, or Cloud Technologies are a plus. At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We’re committed to fostering an inclusive environment where everyone can thrive.