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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer With GenAI - **Company:** Broadmind Designs LLC - **Location:** Dallas, TX, United States - **Experience:** Expert - **Salary:** $118,386.0 - $142,572.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Software Applications, Microsoft Azure, Cloud Computing, Continuous Integration, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Systems, Data Warehousing, Python (Programming Language), Search Technologies, SQL Databases, Data Streaming, Enterprise Data Management, Data Processing, Enterprise Software Applications, Azure Data Factory, Large Language Models, Prompt Engineering, Apache Spark, Generative AI, Git, Build Management, AI Platforms, Kubernetes, HuggingFace, Data Management, Restful APIs, Data Pipelines, Automation Anywhere, Docker, Databricks - **Published:** August 2, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=2f790ceb1de06dfe ## About the Role * 10+ years of experience in Data Engineering. * Strong experience with Python, SQL, Spark, and Databricks. * Experience building ETL/ELT pipelines and data integration solutions. * Hands-on experience with Azure, AWS, or GCP cloud platforms. * Experience with Generative AI, Large Language Models (LLMs), Prompt Engineering, and RAG. * Experience with LangChain, LangGraph, LlamaIndex, or similar AI frameworks. * Experience with OpenAI, Azure OpenAI, AWS Bedrock, Anthropic, or Hugging Face. * Knowledge of Vector Databases such as Pinecone, FAISS, or ChromaDB. * Experience with REST APIs, Git, Docker, Kubernetes, and CI/CD. * Strong communication, analytical, and problem-solving skills. ## Description We are looking for an experienced Data Engineer with Generative AI experience to design and build scalable data pipelines and AI-powered data solutions. The ideal candidate should have strong expertise in Python, SQL, Spark, Databricks, ETL/ELT, Cloud Platforms, and Generative AI technologies. You will work closely with Data Scientists, AI Engineers, and Business Teams to develop data platforms, integrate Large Language Models (LLMs), build RAG applications, and deliver production-ready AI solutions., * Design, develop, and maintain scalable ETL/ELT data pipelines using Python, SQL, and Spark. * Build and optimize data processing solutions using Databricks, Azure Data Factory, or similar tools. * Develop and maintain data lakes, data warehouses, and enterprise data platforms. * Build AI-powered applications using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). * Develop AI workflows using LangChain, LangGraph, LlamaIndex, or similar frameworks. * Integrate OpenAI, Azure OpenAI, AWS Bedrock, or Hugging Face models into enterprise applications. * Work with vector databases such as Pinecone, FAISS, or ChromaDB for semantic search and AI solutions. * Optimize data pipelines, SQL queries, and Spark jobs for performance and scalability. * Build proof-of-concept (POC) solutions and evaluate new AI tools, models, and frameworks. * Collaborate with Data Scientists, AI Engineers, Product Owners, and Business Teams to deliver AI-driven data solutions. * Develop REST APIs and integrate AI services into enterprise applications. * Support CI/CD pipelines, automation, deployment, monitoring, and production support. * Document technical designs, data flows, and implementation processes. ## Related Videos - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) - [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) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [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) - [Accelerating GenAI Development: Harnessing Astra DB Vector Store and Langflow for LLM-Powered Apps](https://www.wearedevelopers.com/videos/966-accelerating-genai-development-harnessing-astra-db-vector-store-and-langflow-for-llm-powered-apps) - [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 - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Got AI ideas but no money? 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