Data Engineer- Manager

Overview As a Data Engineer in KPMG’s Audit Technology Alliance, you design and build data pipelines to convert structured and unstructured client data into high-quality inputs for AI solutions. You establish best practices for data processing and collaborate with AI and solution architecture teams to define data schemas for AI orchestration. You will support Retrieval-Augmented Generation workflows and ensure data quality for reliable AI outputs. This role blends data engineering with AI enablement in a renowned professional services environment, offering the chance to shape how AI-driven insights are produced at scale. Compensation / Benefitscomprehensive benefits packagemedical and dental plansvision coverage401(k) planswell-being benefitspaid time off ResponsibilitiesDesign and implement data pipelines for context engineeringDefine data schemas and contextual payloads for AI orchestration frameworksSupport RAG and context engineering pipelines from audit knowledge sourcesDevelop validation frameworks to ensure data quality and reliable AI outputsPrototype and evolve data engineering strategies to handle complex data relationshipsCollaborate with AI and solution architecture teams to align on data integration for AI workflowsPromote data engineering best practices and standardization Key requirementsMinimum five years of data engineering experience with AI-driven or advanced analytics systemsBachelor’s degree (or equivalent) with preferred Master in CS/Engineering/IS or related fieldDeep expertise in building pipelines for structured and unstructured dataExperience with cloud platforms like Databricks and Microsoft FabricHands-on knowledge of RAG systems and Azure AI SearchStrong Python programming skills and experience with microservice architecturesProficiency with Agile methodologies and SDLC tools (Azure DevOps, Git, CI/CD)problem-solvingindependent ownershipclear communicationPythondata pipelines (ETL/ELT)RAG systems