Director, Data Engineering

Greystar is a leading global real estate platform specializing in property management and development. The Director of Data Engineering will manage strategic projects, drive efficiencies within the data engineering team, and ensure the implementation of best practices in DataOps and MLOps to support data-driven decision-making across the organization.

Responsibilities:

• Provide strategic technology leadership and champion architectural design patterns and practices to grow the existing Enterprise Data Platform
• Guide, collaborate with, and train various Analytics teams (data consumers) to optimize existing design patterns and advance Data as a Product to serve business users with one version of truth
• Lead the development and implementation of data engineering standards and best practices across the organization
• Implement and promote best practices in Data Observability, DataOps and MLOps to ensure efficient and scalable execution of data pipelines in production environment
• Manage and oversee strategic projects, ensuring alignment with business goals and objectives
• Collaborate with cross-functional teams, including marketing, IT, and customer service, to drive data-driven decision-making and innovation
• Provide guidance and mentorship to data engineers, fostering a culture of continuous learning and improvement
• Stay current with industry trends and advancements in data engineering, DataOps, and MLOps to drive innovation and maintain a competitive edge

Requirements:

• Bachelor's/Master's degree from an accredited college or university preferred in Computer Science, Computer Engineering, or a related field
• 10+ years of experience in data engineering, with a focus on data architecture, strategic project management and implementation of best practices
• Strong business acumen, ideally with existing working knowledge of Real Estate and/or Property Management
• Proven experience in leading and managing data engineering teams
• Strong product management capabilities to set priorities, align with department strategy, and drive execution and accountability
• Knowledge of data governance practices and technology related to the management of enterprise information assets
• Excellent communication, presentation, and interpersonal skills
• Ability to break down complex problems and projects into manageable goals
• Proficiency in SQL, PySpark, Python and Databricks platform
• Proficiency in data modeling, analytics, and business intelligence
• Strong understanding and hands-on experience with DataOps, MLOps, Data Quality, and other areas of Data Observability practices to ensure efficient and scalable data operation processes
• Strong understanding of data governance practices and technology related to the management of enterprise information assets
• Experience with DevOps practices, including code management and data quality. Working knowledge of Agile software development methodologies
• Skills in PowerBI or similar tool for data visualization and business storytelling with data