Job Description
As the Head of Data you will be responsible for leading centralized Data functions for Square including Data Science + Analytics, Machine Learning, and Data Engineering teams and will be the architect of Square’s Data strategy. This role will report to the Head of Engineering & Data.
You will:
- Drive the strategic direction and technical roadmap for Square’s data platform, ensuring scalability, reliability, and precision in data handling.
- Oversee the GTM Data, Data Science & Analytics, Data Engineering, and Machine Learning functions, ensuring they align with Square’s strategic objectives.
- Establish core principles for data governance at Square, setting standards for data access, accuracy, and timeliness across all data-centric teams.
- Cultivate a culture of agility, transparency, and continuous enhancement, driving product innovation and operational excellence.
- Deliver impactful insights to cross-functional partners, informing decisions and driving business performance.
- Ensure customer-focused data practices within your teams, aligning data engineering and analytics efforts with customer needs and experiences.
- Attract, develop, and maintain a top-tier data team, scaling capabilities to meet Square’s evolving data demands.
Qualifications
- 15+ years relevant experience in data related fields: Data Analytics, Data Engineering, and/or Machine Learning; 10+ years of experience managing scaled data teams.
- Demonstrated experience in leading data-focused teams, with a proven track record of developing talent and building high-performing data organizations.
- Extensive experience in leading data teams (data science, analytics, and data engineering) with a solid foundation in deploying advanced data strategies in corporate settings.
- Proven ability to build influential relationships and drive data-centric decision-making across product and functional teams.
- Adept at leading cross-disciplinary projects, showcasing an ability to foster collaboration and drive outcomes across various business units.
- Deep understanding of data architecture principles and best practices, with a strategic mindset towards building scalable data ecosystems.
- Proficiency in a range of data technologies and tools (such as SQL, Looker, and Python) with a focus on developing the technical acumen of the team in these areas.
- Experience in applying a spectrum of data science methodologies to address real-world business problems, from statistical analysis to machine learning, enhancing product value and customer experience.
- Ability to clearly and effectively communicate the value of data to leadership and all levels of the organization.
- Excellent communication skills and can articulate a strategy in a concise manner to ensure stakeholders feel included, informed, and aligned on expectations.