VP, Data Engineering

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Requirements:

• 10+ years of experience leading data-focused engineering teams.
• 5+ years of data science and machine learning experience.
• Experience working with stakeholders at an executive level.
• Expert grasp of data engineering including data architecture design, data pipeline development, data modeling, data quality, and governance.
• Hands-on experience with columnar data warehouses and business intelligence tools.
• Understanding of modern ML infrastructure and tooling for data initiatives.
• Knowledge of principles, methodologies, and tools in data engineering & analytics.
• A track record of human-first management while maintaining urgency.
• Excellent listening and communication skills suitable for remote work.

Responsibilities:

• Directly manages data engineering leadership and some engineering directs through 1:1s, coaching, and feedback.
• Takes ownership for all aspects, including infrastructure and architecture of the data platform within the data ecosystem.
• Sets the vision and strategy for the data platform with input from Data and AppDev Engineering Leadership.
• Supports Data Leadership to maintain and evolve engineering best practices.
• Partners with Product and Data Leadership to develop team roadmaps and assure delivery of agreed initiatives.
• Defines and owns product health metrics with input from Data Leadership.
• Provides technical guidance and stays informed on industry best practices.
• Partners across the engineering department to assure alignment with standards and vision.
• Supports cross-functional teams for productive work with effective prioritization and resourcing.
• Owns technical relationships with key vendors and supports contract review.
• Hires, onboards, manages a diverse team while fostering an inclusive environment.
• Maintains a culture that balances urgency with the need for downtime.