AI-Driven Analytics Engineer: Build Data Products

Greystar; Raleigh (NC); On-site; USD 92,000 - 130,000; Full time

Benefits offered by this job

401(k) with Company Match

6-Week Sabbatical

Paid Parental Leave

Onsite housing discount

Job summary

Greystar is building the data foundation to power AI-enabled decision making in global multifamily real estate. As an Analytics Engineer on Decision Intelligence, you will turn data foundations into working data products—dashboards, models, or lightweight web apps—used by business teams daily.

You will work with engineers, designers, and product leaders, showing strong SQL, Python, and Databricks skills, and you will present findings to operators and executives.

Qualifications

• 3+ years in a high-performing analytics or data team with end-to-end ownership.
• Academic background in a quantitative field or equivalent experience.
• Advanced SQL and data modeling with emphasis on grain and keys.
• Strong Python skills for data analysis and tooling.
• Experience with a modern lakehouse/warehouse (Databricks preferred).
• Familiarity with ML techniques and BI tools (Power BI, Tableau, Qlik).
• Ability to design experiments and communicate findings to stakeholders.

Responsibilities

• Own data product initiatives from question to deployment and handoff.
• Build data models and dashboards, iterate with users, and scale to GPS/Podium.
• Collaborate with engineers, analysts, and product managers on AI patterns.
• Ensure data quality, governance, and trustworthy analytics.

Skills

Analytic engineering

End-to-end ownership

SQL

Python

Databricks

Power BI

Experiment design

Communication to stakeholders

AI tooling usage

Education

Quantitative field background (Analytics, CS, Applied Math, Economics, Statistics)

Tools

Databricks

SQL

Python

Power BI

Tableau

Qlik

Streamlit

Azure Synapse

Git

CI/CD

Job description

Greystar is building the data foundation to power AI-enabled decision making in global multifamily real estate. As an Analytics Engineer on Decision Intelligence, you will turn data foundations into working data products—dashboards, models, or lightweight web apps—used by business teams daily.

You will work with engineers, designers, and product leaders, showing strong SQL, Python, and Databricks skills, and you will present findings to operators and executives.