Senior Data Engineer

Newmark; Chicago (IL); Hybrid; USD 190,000 - 230,000; Full time

Job summary

Newmark in Chicago, IL is seeking a Senior Data Engineer with Full Stack capabilities to own cloud-native platforms end to end, spanning front-end experiences, backend services and data layers. You will set technical direction, design scalable systems and drive AI-enabled automation to accelerate delivery.

You will design and maintain data pipelines using Azure Databricks, collaborate with cross-functional teams, mentor engineers, and ensure security and governance across the stack.

Qualifications

• 12+ years in data engineering with hands-on Azure Databricks experience.
• Strong expertise with Azure Databricks, Data Factory, and Data Lake Storage.
• Proficient in Python and SQL; solid distributed systems design and API concepts.

Responsibilities

• Design and maintain scalable data pipelines on Azure Databricks.
• Partner with business and research teams to translate data requirements into designs.
• Lead ingestion, transformation, modeling, and orchestration for large datasets.
• Optimize Spark performance, reliability, and cost; tune pipelines.
• Build batch and near real-time data processing workflows.
• Establish data quality, monitoring, and operational support.
• Mentor engineers and raise architectural standards across teams.
• Own frontend, backend, and data layer integration in a cloud-native stack.
• Architect multi-agent AI workflows and ensure governance across systems.

Skills

Azure Databricks

Python

SQL

Distributed systems

API design

Cloud platforms

Data modeling

DevOps

Mentoring

Education

Bachelor's degree in CS/Engineering

Tools

Docker

Kubernetes

LangChain

AutoGen

Semantic Kernel

MCP

Job description

Job Title: Senior Data Engineer/Full Stack

Location: Hybrid Chicago, IL

Firm Overview:

Newmark Group, Inc. (Nasdaq: NMRK), together with its subsidiaries(“Newmark”), is a world leading commercial real estate advisor and service provider to large institutional investors and other owners, global corporations and other occupiers, and lenders. Built with purpose and driven by excellence, Newmark’s comprehensive platform is uniquely tailored to provide superior outcomes to clients. For the twelve months ended June 30, 2026, Newmark generated revenues of more than $3.6 billion. As of June 30, 2026, Newmark and its business partners together operated from over 195 offices with more than 10,000 professionals across four continents. Learn more at nmrk.com or follow @newmark.

Responsibilities:

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.

Basic Qualifications

• 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:

• 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.

Salary:

The expected base salary for this position ranges from $190,000 to $230,000 annually. The actual base salary will be determined on an individualized basis considering a wide range of factors including, but not limited to, relevant skills, experience, education, and, where applicable, licenses or certifications held. In addition to base salary and a competitive benefits package, this position may be eligible for additional types of compensation including discretionary bonuses and other short- and long-term incentives (e.g., deferred cash, equity, etc.).