Data Engineer
US$135,000 – US$160,000 / yr base salary
Posted 5 Jun 2026
Advertised as “Lead Data Engineer”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 12+ yrs
- Management level
- People management
- Employment
- On-Site
- Contract
- Full-time
| Base salary | US$135,000 – US$160,000 / yr |
|---|
Field of studyComputer Science, Engineering (or related)
Study levelBachelor's
Company Description
Who We Are
AIR Communities is a Multifamily Real Estate Operator headquartered in Denver, CO. We are one of the country's largest owners and operators of multifamily housing, managing high-quality properties in most major markets. At AIR, we value integrity, respect, collaboration, customer focus, and performance. These values are brought to life by our teammates, who are ultimately responsible for our success. When you join our team, you'll work alongside the most dedicated professionals in the industry and open the door to unlimited career opportunities.
AIR is preparing for growth in 2026! We are adding to several departments in our Denver Headquarters with our anticipated growth. Are you ready to take on a new challenge?
Where You Will Work
Our corporate office is located in the Denver Tech Center. Our office spans the top two floors of the building and features expansive views of the mountains and the downtown skyline.
AIR values relationships and the benefits from working side by side with teammates, therefore this position will be in-office 5 days a week to support operations.
Job Description
Job Description
We are seeking a highly skilled Lead Data Engineer to join our dynamic data team. The ideal candidate has extensive experience designing, building, and optimizing modern data pipelines and cloud‑based data platforms. In this role, you will help shape scalable data infrastructure that supports analytics, machine learning, and business‑critical applications across the organization.
What you will do:
- Design, develop, and maintain scalable data pipelines to ingest, transform, and deliver large and diverse datasets.
- Write efficient, reusable SQL and/or Python for data ingestion, transformation, and integration.
- Optimize data workflows for performance, reliability, security, and cost‑efficiency in cloud environments.
- Collaborate with data scientists, analysts, application teams, and business stakeholders to understand data requirements and deliver technical solutions.
- Implement data governance and security practices across pipeline components and data assets.
- Monitor data flows, troubleshoot issues, and ensure data quality, availability, and integrity.
- Integrate data from various internal and external sources into centralized data platforms.