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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer- Manager - **Company:** Kpmg LLP - **Location:** Washington, DC, United States - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Microsoft Azure, Information Systems, Computer Programming, Continuous Integration, Data Cleansing, Information Engineering, Data Systems, Python (Programming Language), Knowledge-Based Systems, Systems Development Life Cycle, Message Oriented Middleware, Search Technologies, Unstructured Data, Multi-Agent Systems, Generative AI, Git, Microsoft Fabric, Information Technology, Virtual Agents, Data Pipelines, Databricks, Microservices - **Published:** June 9, 2026 - **Apply:** https://diversityjobs.com/career/17189903/Data-Engineer-Manager-D-C-Washington ## About the Role * Minimum fiveyears of recent professional experience in data engineering, with a proventrack recordof building data solutions that support AI-driven or advanced analytics systems * Bachelor's degree from an accredited college or university;master's degree from an accredited college or university in Computer Science, Engineering, Information Systems, or a related field is preferred * Deepexpertisein designing and building data pipelines that process both structured and unstructured data, preparing it for advanced AI consumption using cloud platforms like Databricks and Microsoft Fabric * Demonstrated experience in data preparation and structuring for Retrieval-Augmented Generation (RAG) systems, with hands-on knowledge of tools like Azure AI Search and a strong understanding of how data integrates into AI agent workflows * Strong, independent programming skills in Python andsignificant experiencewith microservice architecture, including building data APIs and interacting with asynchronous messaging systems * Proficiency with Agile methodologies and SDLC tools (Azure DevOps, Git, CI/CD) combined with excellent problem-solving skills to articulate complex data concepts and influence technical direction (200TEC) ## Description * Take ownership of designing and implementing data pipelines focused on context engineering, transforming vast amounts ofstructured(e.g., transactional) and unstructured client data into high-quality inputs for our AI solutions * Set the standard for data engineering excellence,establishingand evangelizing best practices for processing and modeling diverse data sets to be analyzed by advanced generative AI agents * Serve as a key subject matter expert, collaborating closely with AI and solution architecture teams to define and deliver the specific data schemas and contextual payloads required by our AI orchestration frameworks * Support the development ofRetrieval-Augmented Generation (RAG)and context engineering pipelines from audit knowledge sources and the integration into AI agent workflows; design and implement the use of metadata across knowledge systems to drive the use of context * Champion data quality by developing and implementing rigorous validation frameworks to ensure the reliability of all data sources, which is critical for generating verifiable AI outputs * Drive the product forward by personally prototyping and evolving our data engineering strategies, pioneering innovative techniques to handle complex data relationships andkeepour context engineering capabilities state-of-the-art * Act with integrity, professionalism, and personal responsibility to uphold KPMG's respectful and courteous work environment ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [The Data Mesh as the end of the Datalake as we know it](https://www.wearedevelopers.com/videos/156-the-data-mesh-as-the-end-of-the-datalake-as-we-know-it) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)