Analytics Engineer, SFR Real Estate

Evergreen Residential is a high growth Real Estate Company and institutional investment platform in the single-family residential ('SFR') and build-to-rent (“BTR”) sectors. We are committed to changing the way investors own and manage SFR homes, and to building a modern way to deliver the data, tools and services that enable our clients to invest in the world’s largest asset class at scale. Our team is collaborative, open-minded and curious. Transparency is a core value, we speak our minds, are responsible for our actions and celebrate our wins. We are serious about our business, but we don't take ourselves too seriously.
We offer a flexible, empowering culture, competitive compensation and benefits, and the opportunity to work with and learn from industry pioneers and experts.
If you are self-motivated and mission driven with a ‘can do’ mindset and see solutions where others may see problems, come and grow with us!
We are committed to changing the way investors own and manage SFR homes, and to building a modern way to deliver the data, tools and services that enable our clients to invest in the world’s largest asset class at scale. This is a highly cross-functional role: you will work directly with the business to understand its logic and needs, build data models in our analytics warehouse, and use those models to create dashboards and answer business questions. While the work spans teams, data models are your primary work product. Initial focus is modeling data from our property management system and purchased external market data to create one source of truth for reporting and analysis. For Post- This is a full-time employee role based in our Dallas office (4 days in office, 1 day remote). The Company is unable to provide visa sponsorship.
Resumes will only be considered if the additional information questions are answered.
The Role: The role includes, but is not limited to, the following responsibilities:
Partnering with business stakeholders to understand business logic, drivers and needs, and translating them into consistent, well-defined metrics
Developing and maintaining data models that transform data from our property management system and external market data sources into a clean, centralized analytics warehouse in Snowflake
Writing tests and documentation to ensure data accuracy and reliability
Building dashboards and analyses on top of those models to answer business questions and support decision-making
Participating in code review and contributing to the standards and conventions of our dbt project
Being a resource for improving data proficiency throughout the organization
Staying up to date with emerging trends and technologies in analytics engineering
What You Will Bring to the Table:
Bachelor’s Degree in a relevant field preferred, or equivalent practical experience
Minimum 5 years of experience in analytics engineering, data analytics, business intelligence or a related field, including at least 1 year building dbt models in production
Experience working in an AI-first development environment (e.g., using AI coding assistants and agents to write, test and review code)
Strong SQL skills and a solid background in data modeling (dimensional modeling preferred) and analytics engineering best practices
Experience with dbt and Snowflake or a similar cloud data warehouse and at least one BI/dashboarding tool; experience with Tableau and/or Python a plus
Experience working in Git with pull request-based development workflows
Experience in real estate investment and/or rental sector desirable, including familiarity with property management system data
A proven problem solver, comfortable turning ambiguous business questions into clear data models, with a sound understanding of technical tradeoffs
Collaborative team player, you are truly a “do-er”, happy to be a hands-on problem-solver to move the data program forward
Excellent communication skills – verbal and written
Please do not rely on compensation estimates for our jobs that are posted on sites other than our direct website as these may be misleading.
About Evergreen Residential
Founded in 2021, Evergreen Residential is a full-service SFR platform leveraging proven operational practices and the latest technological advances to optimize investor returns and achieve positive outcomes for our residents and the communities in which we operate. We offer a full suite of services, including Investment Management, Asset Origination, and Advisory Services. The firm is headquartered in Dallas with offices in New York City.
The leadership team has extensive experience dating back to the early institutionalization of SFR and unrivaled depth of experience in the complete asset life cycle. We are built to withstand changing market conditions, and our business produces resilient, predictable cash flows and margins. We are committed to charting new paths and using data to achieve best-in-class results. Our business is evergreen.
Beyond financial returns, the Company is committed to measurable impact objectives. We believe that inclusive and equitable management, environmentally sustainable long-term strategies, and resident-focused policies are good business - for our residents, our investors, and our team. We are committed to using environmentally sustainable practices and empowering our residents to improve their financial health.
Our cornerstone values - Accountability, Transparency and Partnership - are built on a foundation of Integrity and provide the roadmap for our daily actions, interactions and decisions.
Equal Opportunities and Other Employment Statements
We are deeply committed to building a workplace and community where inclusion is not only valued but prioritized. We take pride in being an equal opportunity employer and seek to create a welcoming environment based on mutual respect, and to recruit, develop and retain the most talented people from a diverse candidate pool. All employment decisions shall be made without regard to race, color, religion, gender, gender identity or expression, family status, marital status, sexual orientation, national origin, genetics, neurodiversity, disability, age, or veteran status, or any other basis as protected by federal, state, or local law.