Backend AI-Forward Data Engineer

About the Role

The role requires a deep understanding of data engineering principles, AI systems, and cloud technologies. You will be responsible for building and maintaining scalable data pipelines, developing data models optimized for analytical queries and AI consumption, and implementing data quality frameworks.

Greystar's D2AI team is responsible for the platforms, processes, and practices that power AI across the organization. As a member of this team, you will have the opportunity to work with a talented group of engineers, designers, and product leaders who have experience from top companies like Google, Microsoft, and Amazon.

What You Will Do

• Design, build, and maintain scalable data pipelines that ingest, transform, and serve data from dozens of source systems
• Develop and operate the Data Management Platform (DMP) on Databricks, ensuring data is governed, validated, and available for AI/ML workloads
• Build data models optimized for both analytical queries and AI consumption, including feature stores, embedding pipelines, and real-time serving layers
• Implement data quality frameworks, including automated testing, lineage tracking, anomaly detection, and regression testing for critical data assets
• Enable AI and MCP integrations by building and maintaining MCP server integrations that expose Greystar's data to LLM-powered tools and AI agents
• Design APIs and data interfaces that allow AI products to query and act on data in real-time
• Partner with Data Science and Product teams to operationalize ML models, building and maintaining the necessary data infrastructure
• Collaborate with engineering, analytics, and business teams to ensure AI solutions are reliable, responsible, and impactful
• Develop and maintain documentation for data pipelines, data models, and data quality frameworks
• Stay up-to-date with the latest developments in AI, data engineering, and cloud technologies, applying this knowledge to continuously improve Greystar's data infrastructure

What We Are Looking For

• 5+ years of experience in data engineering, with a focus on building scalable data pipelines and data infrastructure
• Strong understanding of AI systems, including design, development, and operationalization
• Experience with cloud technologies, including Databricks, AWS, or GCP
• Proficiency in programming languages such as Python, Java, or Scala
• Experience with data modeling, data warehousing, and data governance
• Strong understanding of data quality frameworks, including automated testing and anomaly detection
• Experience with collaboration tools such as Git, Jira, and Slack
• Excellent communication and problem-solving skills
• Ability to work in a fast-paced environment, prioritizing multiple projects and deadlines

Nice to Have

• Experience with machine learning frameworks, including TensorFlow or PyTorch
• Knowledge of containerization technologies, including Docker or Kubernetes
• Experience with agile development methodologies, including Scrum or Kanban
• Certification in data engineering, AI, or a related field

Benefits and Perks

• Competitive salary and benefits package
• Opportunity to work on large-scale AI projects with a talented team of engineers and data scientists
• Collaborative and dynamic work environment
• Flexible working hours and remote work options
• Professional development opportunities, including training and conference attendance
• Access to cutting-edge technologies and tools
• Recognition and reward for outstanding performance
• Comprehensive health and wellness benefits, including medical, dental, and vision insurance
• Retirement savings plan with company match
• Generous paid time off and holiday schedule

• Develop a strong understanding of AI systems, including design, development, and operationalization, to stand out in this role.
• Create a portfolio of your work, including examples of data pipelines, data models, and data quality frameworks you have developed.
• Be prepared to demonstrate your experience with AI tools and technologies, such as Databricks, AWS, or GCP, during the interview process.
• Emphasize your ability to work collaboratively with cross-functional teams, including engineering, analytics, and business teams.
• Research Greystar's company culture and values, and be prepared to discuss how your skills and experience align with these principles.
• Don't be afraid to ask questions during the interview process, such as what a typical day looks like in this role, or what opportunities there are for professional development and growth.