Senior Data Engineer — AI-Ready Platform

Greystar; United States; Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Generous PTO

401(k) with Company Match

Paid Parental Leave

Onsite housing discount

Job summary

Greystar is seeking a Senior Data Engineer to design, build, and operate the core data infrastructure powering AI-enabled analytics across a multi-billion-dollar global portfolio. You’ll own end-to-end data pipelines, ensure data governance, and enable AI integrations with MCP and related tools.

You’ll collaborate with data science, product, and engineering teams to deploy scalable, production-grade data assets and maintain high data quality across many source systems and domains.

Qualifications

• 5+ years of professional data engineering experience
• Deep expertise with Databricks, Spark, or similar distributed data processing frameworks
• Strong SQL skills and data modeling for analytical and AI workloads

Responsibilities

• Take assigned initiatives from raw ingestion through bronze, silver, and certified gold, staying with the work through deployment and handoff to operations.
• Redeploy across projects as priorities shift, ramping quickly on unfamiliar source systems and business domains.
• Design, build, and maintain scalable and self-healing data pipelines that ingest, transform, and serve data from dozens of source systems.
• Build data models with correct grain, keys, and referential integrity for AI/ML workloads.
• Implement data quality frameworks including automated testing, lineage tracking, anomaly detection, and regression testing.

Skills

Databricks

SQL

Python

Airflow

PostgreSQL

AI tooling

Spark

Tools

Git

CI/CD

Terraform

dbt

Delta Lake

Unity Catalog

Monte Carlo

Azure Synapse

Job description

Greystar is seeking a Senior Data Engineer to design, build, and operate the core data infrastructure powering AI-enabled analytics across a multi-billion-dollar global portfolio. You’ll own end-to-end data pipelines, ensure data governance, and enable AI integrations with MCP and related tools.

You’ll collaborate with data science, product, and engineering teams to deploy scalable, production-grade data assets and maintain high data quality across many source systems and domains.