Director, Data Engineering

ABOUT GREYSTAR

Greystar is a leading, fully integrated global real estate platform offering expertise in property management, investment management, development, and construction services in institutional-quality rental housing. Headquartered in Charleston, South Carolina, Greystar manages and operates over $300 billion of real estate in more than 250 markets globally with offices throughout North America, Europe, South America, and the Asia-Pacific region. Greystar is the largest operator of apartments in the United States, managing over 1,000,000 units/beds globally. Across its platforms, Greystar has nearly $79 billion of assets under management, including over $35 billion of development assets and over $30 billion of regulatory assets under management. Greystar was founded by Bob Faith in 1993 to become a provider of world-class service in the rental residential real estate business. To learn more, visit www.greystar.com.

JOB DESCRIPTION SUMMARY

The Director of Data Engineering is responsible for managing strategic projects and driving efficiencies across the data engineering team. The candidate should possess a strategic mindset, sound business acumen, and a deep understanding of DataOps, MLOps, and other data-related areas to elevate data-driven culture across the organization. Strong leadership and communication skills with the ability to influence and drive data strategy are essential. A leader with a collaborative, customer-facing attitude will thrive in this role, frequently interfacing with the Data Governance, Analytics, and Data Science teams.

JOB DESCRIPTION

KEY 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

BASIC KNOWLEDGE & QUALIFICATIONS:

• 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.

SPECIALIZED SKILLS:

• Data Engineering Skills: Proficiency in SQL, PySpark, Python and Databricks platform.
• Data Modeling and Analytics: Proficiency in data modeling, analytics, and business intelligence.
• Data Observability: 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.
• Data Governance: Strong understanding of data governance practices and technology related to the management of enterprise information assets.
• DevOps: Experience with DevOps practices, including code management and data quality. Working knowledge of Agile software development methodologies.
• Data Visualization: Skills in PowerBI or similar tool for data visualization and business storytelling with data.

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