Senior Data Engineer, AI & Data Platform

Experteer Overview In this Senior Data Engineer role, you build and operate the core data infrastructure that powers AI-enabled products and analytics across Greystar’s global portfolio. You work across the Data Management Platform and AI-enabled tools to ensure data is accessible, trustworthy, and ready for AI workloads. You own initiatives end-to-end, adapt to changing priorities, and collaborate with engineering, analytics, and business teams to deliver reliable, scalable solutions. This is a fast-moving, AI-forward team offering broad business exposure and impactful projects. Compensation / Benefits * Take initiatives from raw ingestion through bronze, silver, and certified gold, including deployment and handoff to operations * Redeploy across projects as priorities shift and learn new business domains quickly * Build scalable, self-healing data pipelines ingesting data from numerous source systems * Develop and operate the Data Marketplace on Databricks with data governance and high quality * Create robust data models with correct grain, keys, and referential integrity for AI tools and data catalogs * Build AI-ready data infrastructure including feature stores, embeddings, and real-time serving layers * Implement data quality frameworks with automated testing, lineage, anomaly detection, and regression tests * Develop MCP server integrations and APIs for real-time data access by AI products * Collaborate with Data Science and Product teams to operationalize ML models and monitoring * Establish data governance, access controls, PII handling, and compliance; document models and pipelines for self-service Tasks * 5+ years of professional data engineering experience * Deep expertise with Databricks, Spark, or similar frameworks * Strong SQL and data modeling across analytical and AI/ML workloads * Experience with AI coding tools ( Cursor, Codex, Claude Code, etc.) * Proficiency in Python; orchestration tools (Airflow, Dagster, Databricks Workflows) * Cloud data platforms (ADLS, Synapse, Azure ML; AWS/GCP acceptable) and Postgres * Experience building ML infrastructure (feature stores, training pipelines, model serving) * Familiarity with LLM integration patterns, vector databases, MCP, and RAG * Understanding of AI governance: data provenance, bias detection, responsible AI data practices * Clear communicator with ability to explain architecture to product and business stakeholders Key requirements * Competitive medical, dental, vision insurance * Generous PTO: 15 days vacation, 4 personal days, 10 sick days, 11 holidays * Onsite housing discount for onsite roles * 6-week paid sabbatical after 10 years * 401(k) with 6% match * Parental leave and fertility benefit reimbursement

Experteer Overview In this Senior Data Engineer role, you build and operate the core data infrastructure that powers AI-enabled products and analytics across Greystar’s global portfolio. You work across the Data Management Platform and AI-enabled tools to ensure data is accessible, trustworthy, and ready for AI workloads. You own initiatives end-to-end, adapt to changing priorities, and collaborate with engineering, analytics, and business teams to deliver reliable, scalable solutions. This is a fast-moving, AI-forward team offering broad business exposure and impactful projects. Compensation / Benefits * Take initiatives from raw ingestion through bronze, silver, and certified gold, including deployment and handoff to operations * Redeploy across projects as priorities shift and learn new business domains quickly * Build scalable, self-healing data pipelines ingesting data from numerous source systems * Develop and operate the Data Marketplace on Databricks with data governance and aa

• quality * Create robust data models with correct grain, keys, and referential integrity for AI tools and data catalogs * Build AI-ready data infrastructure including feature stores, embeddings, and real-time serving layers * Implement data quality frameworks with automated testing, lineage, anomaly detection, and regression tests * Develop MCP server integrations and APIs for real-time data access by AI products * Collaborate with Data Science and Product teams to operationalize ML models and monitoring * Establish data governance, access controls, PII handling, and compliance; document models and pipelines for self-service Tasks * 5+ years of professional data engineering experience * Deep expertise with Databricks, Spark, or similar frameworks * Strong SQL and data modeling across analytical and AI/ML workloads * Experience with AI coding tools ( Cursor, Codex, Claude Code, etc.) * Proficiency in Python; orchestration tools (Airflow, Dagster, Databricks Workflows) * Cloud data aaaa days, (ADLS, Synapse, Azure ML; AWS/GCP acceptable) and Postgres * Experience building ML infrastructure (feature stores, training pipelines, model serving) * Familiarity with LLM integration patterns, vector databases, MCP, and RAG * Understanding of AI governance: data provenance, bias detection, responsible AI data practices * Clear communicator with ability to explain architecture to product and business stakeholders Key requirements * Competitive medical, dental, vision insurance * Generous PTO: 15 days vacation, 4 personal days, 10 sick days, 11 holidays * Onsite housing discount for onsite roles * 6-week paid sabbatical after 10 years * 401(k) with 6% match * Parental leave and fertility benefit reimbursement