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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** Newmark ltd - **Location:** Schiller Park, IL, United States - **Experience:** Expert - **Salary:** $190,000.0 - $230,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), JavaScript (Programming Language), Artificial Intelligence, Amazon Web Services, Microsoft Azure, C Sharp (Programming Language), Cloud Engineering, Software Quality, Information Engineering, Data Security, Dataspaces, Data Stores, Database Design, DevOps, Programming Tools, Distributed Computing Environment, Distributed Systems, Python (Programming Language), Node.Js, NoSQL, Performance Tuning, Query Optimization, Standard Sql, Azure Data Lake, Next.js, SQL Databases, Systems Integration, TypeScript, Web Application Frameworks, Azure Service Bus, Cloud Platform System, Data Ingestion, Azure Data Factory, LangChain, ReactJS, Large Language Models, Multi-Agent Systems, Apache Spark, Generative AI, Backend, Data Layers, Event Driven Architecture, Containerization, Kubernetes, Information Technology, AutoGen, Apache Kafka, Free and Open-Source Software, Graphql, Front End Software Development, Virtual Agents, Api Design, Stream Processing, Semantic Kernel, Data Pipelines, Docker, AI Co-pilot, Databricks, Microservices - **Published:** October 8, 2026 - **Apply:** https://www.disabledperson.com/jobs/75853673-senior-data-engineer ## About the Role * 12+ years of experience in data engineering or related roles, with significant hands-on experience in Azure Databricks. * Strong expertise with Azure Databricks, Azure Data Factory, Azure Data Lake Storage, and related Azure services. * Advanced proficiency in Python and SQL * Deep understanding of distributed systems design, microservices architecture, and API design (REST/GraphQL). * Strong experience with cloud platforms (Azure, AWS, or GCP) and cloud-native architecture patterns. * Hands-on experience building or integrating agentic AI systems, LLM-powered applications, or AI agent orchestration frameworks (e.g., LangChain, AutoGen, Semantic Kernel, MCP). * Proven track record of leading large-scale technical initiatives across multiple teams. * Strong background in database design, including both relational (SQL) and NoSQL data stores. * Deep understanding of CI/CD pipelines, infrastructure as code, and DevOps practices. * Demonstrated experience designing, deploying, and supporting production-grade data pipelines on a scale. * Solid understanding of distributed data processing, data modeling, and performance optimization. * Excellent problem-solving skills and ability to operate independently in complex environments. * Strong communication skills and comfort working with both technical and business stakeholders. * Demonstrated ability to mentor engineers and influence technical direction without direct reporting authority. Preferred Qualifications: * Expert-level proficiency in modern JavaScript/TypeScript frameworks (e.g., React, Next.js) and backend languages (e.g., C#, Node.js, Java, or similar). * Experience designing multi-agent systems, tool-calling architectures, or retrieval-augmented generation (RAG) pipelines. * Experience with event-driven architecture and real-time data processing (e.g., Kafka, Event Hubs, Kinesis). * Familiarity with containerization and orchestration technologies (Docker, Kubernetes). * Prior experience in commercial real estate, fintech, or operations/transaction systems. * Track record of speaking, writing, or open-source contributions that demonstrate technical thought leadership, especially in applied AI. Education: Bachelor's degree in computer science, Engineering, MIS, or related field preferred. ## Description Newmark's technology team is looking for a Senior Data Engineering with Full stack capabilities to drive the architecture and delivery of the cloud-native platforms end to end, from front-end experiences to backend services and data layers. This role will set technical direction across multiple teams, design high-scale distributed systems, and champion the adoption of agentic AI-driven automation to accelerate engineering velocity and unlock new product capabilities., * Serve as a senior technical contributor responsible for designing and maintaining scalable, production-ready data pipelines using Azure Databricks. * Partner with business and research teams to translate complex data requirements into robust technical designs aligned with enterprise architecture standards. * Lead design decisions around data ingestion, transformation, modeling, and orchestration for large and complex datasets. * Optimize performance, reliability, and cost through effective Spark tuning, query optimization, and pipeline design. * Build and maintain batch and near real-time data processing workflows. * Establish and follow best practices for data quality, monitoring, and operational support. * Support analytics and data science teams by delivering well-modeled, reusable data assets. * Ensure data security, governance, and compliance with organizational standards. * Collaborate with platforms, infrastructure, and security teams to support and evolve the broader data ecosystem. * Mentor junior and mid-level engineers and raise overall engineering standards. * Design, build, and maintain scalable, high-performance web applications and distributed services in a cloud-native environment. * Own and drive the technical architecture for complex, cross-team full-stack initiatives spanning front-end, backend, and data layers. * Architect and integrate agentic AI workflows (autonomous agents, LLM-driven automation, AI copilots) into engineering and product systems to drive efficiency and new capabilities. * Set engineering standards and best practices for code quality, system design, testing, and deployment across the organization, including responsible use of AI-assisted development tools. * Lead technical design reviews and provide architectural guidance to multiple engineering teams. * Partner with product, design, and engineering leadership to translate business strategy into scalable technical roadmaps, including AI-driven product capabilities. * Identify and resolve systemic performance, reliability, and scalability issues across the stack. * Mentor and coach senior and mid-level engineers, raising the technical bar across the organization on both full-stack and AI engineering practices. * Drive adoption of modern frameworks, tools, and engineering practices, including agentic AI and LLM tooling, to improve developer velocity and system resilience. * Maintain awareness of emerging technologies and industry trends, particularly in agentic AI and automation, and assess their applicability to the business.