Senior AI Data Platform Engineer (Remote)

Greystar; United States; Remote; USD 115,000 - 135,000; Full time

Benefits offered by this job

Medical/Dental/Vision

Paid Time Off

401(k) Match

Job summary

Greystar is building the data foundation to power AI-enabled capabilities across a global portfolio. We seek a Senior Data Engineer to design, build, and operate core data infrastructure for AI-powered analytics and decision-making across the organization.

You will work across the Data Management Platform, MCP integrations, and AI-enabled analytics tools, collaborating with engineers, product leaders, and data scientists.

Qualifications

• 5+ years of professional data engineering experience building and operating production data platforms.
• Deep expertise with Databricks, Spark, or similar distributed data processing frameworks.
• Strong SQL skills and data modeling experience across analytical and AI/ML workloads.
• Deep experience with AI coding tools like Cursor, Codex, Claude Code, etc.
• Proficiency in Python; experience with orchestration tools (Airflow, Dagster, or Databricks Workflows).
• Experience with cloud data platforms (ADLS, Synapse, Azure ML; AWS/GCP acceptable) and relational back ends such as Postgres.

Responsibilities

• Own initiatives end to end from ingestion through deployment and handoff to operations.
• Redeploy across projects as priorities shift and ramp quickly on unfamiliar source systems.
• Design and maintain scalable data pipelines ingesting data from dozens of source systems.

Skills

Databricks

Spark

Python

SQL

Data modeling

AI tooling

Tools

Delta Lake

Unity Catalog

dbt

Azure

Postgres

Git/CICD

Job description

Greystar is building the data foundation to power AI-enabled capabilities across a global portfolio. We seek a Senior Data Engineer to design, build, and operate core data infrastructure for AI-powered analytics and decision-making across the organization.

You will work across the Data Management Platform, MCP integrations, and AI-enabled analytics tools, collaborating with engineers, product leaders, and data scientists.