Senior Data Engineer

About the role

Greystar is building the data foundation for an AI‑advanced global multifamily real‑estate operator. The Senior Data Engineer will design, build, and operate core data infrastructure that powers AI‑enabled products, analytics, and decision‑making across the company.

Key responsibilities

• Own end‑to‑end data initiatives from raw ingestion through bronze, silver, and certified gold stages, including deployment and handoff to operations.
• Design, build, and maintain scalable, self‑healing pipelines on Databricks that ingest data from dozens of source systems (PMS, CRM, financial, IoT, web/mobile analytics).
• Develop and operate the Data Marketplace, ensuring data governance, validation, high quality, and availability for AI/ML workloads.
• Build AI‑ready data models, feature stores, embedding pipelines, and real‑time serving layers optimized for both analytical queries and machine‑learning consumption.
• Implement data quality frameworks, automated testing, lineage tracking, and anomaly detection to maintain trusted data assets.

Required profile

• 5+ years of professional data engineering experience building and operating production data platforms.
• Deep expertise with Databricks, Spark (or similar distributed processing frameworks) and strong SQL/data‑modeling skills for analytical and AI/ML workloads.
• Proficiency in Python and experience with orchestration tools such as Airflow, Dagster, or Databricks Workflows.
• Experience with cloud data platforms (Azure ADLS, Synapse, Azure ML; AWS or GCP acceptable) and relational databases like PostgreSQL.

Required skills

• Databricks / Spark
• SQL
• Python
• Airflow or Dagster (or Databricks Workflows)
• Azure data services (ADLS, Synapse, Azure ML) – AWS/GCP equivalents acceptable
• PostgreSQL
• AI coding tools (Cursor, Codex, Claude Code)
• Feature‑store concepts and vector databases (e.g., Pinecone, Weaviate)