VPP-115-Senior Data Engineer USA - Chicago , hybrid

Vekend, Llc; Chicago, Northern (IL, KY); Hybrid; USD 140,000 - 180,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) with company match

Paid time off (PTO)

Flexible work arrangements

Job summary

Vekend, Llc in Chicago seeks a hands-on Senior Data Engineer to design and deliver core capabilities for an enterprise Leasing data platform. You will own data models, build scalable cloud pipelines, and expose governed data via APIs for AI-enabled applications.

In this hybrid role, you’ll collaborate with engineering, product, data science, analytics, and business stakeholders, delivering data products and MCP integrations while ensuring production readiness and cost efficiency.

Qualifications

• Hands-on senior engineer with enterprise data platform delivery experience.
• 7+ years in Data Engineering / Big Data development.
• Strong Linux, Python and SQL skills.
• Experience with cloud data platforms (Azure/AWS) and data modeling.

Responsibilities

• Design and deliver scalable data models and architecture for leasing data.
• Build and modernize cloud data platforms using Azure and/or AWS tools.
• Develop batch and incremental data pipelines with Python, PySpark, and SQL.
• Expose governed data via APIs and MCP integrations for AI/LLM apps.
• Implement data quality, monitoring, and observability for production readiness.
• Collaborate with engineering, product, data science, analytics, and business stakeholders.

Skills

Python

SQL

Data modeling

Big data

Cloud data design

Education

Bachelor's degree

Tools

Azure

AWS

Databricks

PySpark

SQL databases

Job description

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

Who You’ll Work With

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.

What You’ll Do

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 workstreams 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.

What You’ll Bring

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 NoSQL platforms such as Cosmos DB or MongoDB.

Experience designing and building APIs and integration services for enterprise data platforms.

Experience with LLM-driven workflows, RAG architectures, MCP integrations, or preparing enterprise data for AI/agentic consumption.

Demonstrated ability to lead technical workstreams and drive architecture and engineering decisions as a senior individual contributor.

Strong communication skills and ability to work independently within structured project deliverables.

Ability to produce thorough technical documentation and support knowledge transfer

Nice-to-Haves

Experience with Databricks and modern lakehouse architectures.

Experience with streaming technologies such as Kafka, Spark Streaming, or Azure Event Hubs.

Familiarity with vector databases such as Pinecone or Weaviate.

Familiarity with graph or knowledge databases such as Neo4j.

Experience with LLM orchestration frameworks such as LangChain or LlamaIndex.

Knowledge of DevOps and cloud engineering practices, including CI/CD, Terraform, Kubernetes, and containerization.

Experience with data governance, lineage, observability, and compliance frameworks such as GDPR or CCPA.

Exposure to commercial real estate, leasing, CRM, transaction, or deal-pipeline data.

What Makes Us Great Place To Work

Vekend is a people-first organization focused on developing thoughtful products and services that create meaningful impact for our customers and communities. We are committed to fostering a collaborative, respectful, and inclusive work environment where employees are empowered to take ownership of their work, contribute ideas, and grow professionally. We strive to support flexibility and work-life balance while maintaining high standards of performance and accountability.

For all locations, the good-faith, reasonable annualized full-time compensation for this role will be determined based on competitive market data and may vary depending on geographic location, job-related knowledge, skills, experience, education, and other business considerations. Specific compensation details will be discussed during the interview process. Vekend offers a comprehensive benefits and wellness package designed to support employees’ overall well-being, financial security, and professional growth. Eligibility and coverage are subject to the terms of the applicable benefit plans and company policies. Eligible employees have access to medical, dental, and vision insurance with company contributions toward premiums, a 401(k) retirement plan with company matching, and Paid Time Off that begins accruing on the first day of employment. We also support flexible work arrangements and opportunities for professional growth. Benefits eligibility, coverage, and company contributions are subject to the terms of the applicable plan documents and may be modified at the company’s discretion.