VPP--Senior Data Engineer Chicago , hybrid

You will collaborate with engineering, product, data science, analytics, and business stakeholders to design and deliver core capabilities for an enterprise Leasing data platform. This role combines hands-on data engineering with architecture ownership, ensuring the accessibility of enterprise data to modern Agentic AI and LLM-powered applications through APIs and AI-ready data structures.

Department:

AI, Insights, & Solutions

Project Location(s):

USA - Chicago , hybrid

Job Type:

Employee

Education:

Bachelor's

You will collaborate with engineering, product, data science, analytics, and business stakeholders to design and deliver core capabilities for an enterprise Leasing data platform. This role combines hands-on data engineering with architecture ownership, ensuring the accessibility of enterprise data to modern Agentic AI and LLM-powered applications through APIs and AI-ready data structures. This is an hybrid position, with 2 days a week in Chicago office.

Design and deliver core capabilities for an enterprise Leasing data platform.

This role combines hands-on data engineering with architecture ownership, and is responsible for design data models, build scalable cloud-based pipelines and integration services, and consolidate leasing transaction, broker, CRM, and market availability data into a unified, governed data layer.

The role will also help make enterprise data accessible to modern Agentic AI and LLM-powered applications, through APIs, AI-ready data structures, and Model Context Protocol (MCP) integrations.

Key responsibilities:

Design and deliver scalable data models and architecture for leasing transaction, broker, CRM, and market availability data.

Build and modernize enterprise-grade cloud data platforms using Azure and/or AWS technologies, including Databricks, Azure Data Factory, Synapse, AWS Glue, or EMR.

Develop robust batch and incremental data pipelines using Python, PySpark/Spark, and SQL.

Consolidate siloed data sources into a unified, governed cloud data layer.

Design and implement APIs and integration services that expose governed data to enterprise applications and downstream consumers.

Build data products, semantic structures, and MCP/API interfaces that make enterprise data consumable by Agentic AI systems, LLM-powered assistants, RAG workflows, and analytics applications.

Implement automated testing, monitoring, data quality checks, lineage, and observability to ensure production readiness.

Optimize data platforms and pipelines for performance, scalability, maintainability, and cost.

Drive technical and architectural decisions across work streams and contribute to design and code reviews.

Partner with engineering, product, data science, analytics, and business stakeholders to define and deliver platform capabilities.

Own technical deliverables from design through implementation, production handoff, and knowledge transfer.

Create architecture documentation, technical designs, operational runbooks, and structured handoff materials for internal engineering teams.

Hands-on senior engineer with experience delivering complex enterprise data platforms, driving technical decisions independently, and taking solutions from design through production-ready implementation and handoff.

7+ years of experience in Data Engineering and Big Data development, including delivery of multiple large-scale, complex projects.

Strong hands-on experience with Azure and/or AWS cloud data platforms.

Advanced proficiency in Python and SQL.

Deep hands-on expertise with PySpark/Spark for distributed data processing.

Strong experience with data modeling and data architecture.

Experience designing and optimizing relational databases such as Azure SQL or PostgreSQL and…