Senior Data Engineer - AI-Ready Data Platform

Greystar; South Carolina; On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Disability & Life insurance

Paid time off

Sabbatical after 10 years

401(k) with company match

Job summary

Greystar is seeking a Senior Data Engineer to design, build, and operate the core data infrastructure powering AI-driven products and analytics across a global portfolio. You will own data ingestion, transformation, and provisioning from multiple source systems, ensuring data is trustworthy and AI-ready.

You will deploy scalable pipelines, maintain data quality, and collaborate with Data Science and Product teams to operationalize ML models while advancing governance and observability across

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 and Python programming.
• Experience with cloud data platforms (ADLS, Synapse, Azure ML; AWS/GCP acceptable) and relational back ends.
• Familiarity with MCP, LLM integration patterns, and data governance practices.

Responsibilities

• Design, build, and maintain scalable data pipelines for multiple source systems.
• Develop and operate our Data Marketplace (DMP) on Databricks for AI workloads.
• Create robust data models with correct grain and keys for reliable downstream AI tools.
• Build models and feature stores for analytics and AI consumption.
• Collaborate with data science and product teams to operationalize ML models and governance.

Skills

Databricks

Spark

SQL

Data modeling

Python

Airflow

Dagster

Databricks Workflows

AI tooling

Tools

Databricks

Spark

Postgres

Azure Synapse

Azure ML

dbt

Airflow

Dagster

Job description

Greystar is seeking a Senior Data Engineer to design, build, and operate the core data infrastructure powering AI-driven products and analytics across a global portfolio. You will own data ingestion, transformation, and provisioning from multiple source systems, ensuring data is trustworthy and AI-ready.

You will deploy scalable pipelines, maintain data quality, and collaborate with Data Science and Product teams to operationalize ML models while advancing governance and observability across