VP, Data Engineering

Our product and technology teams, including the data teams at Axios, enable our mission of delivering the cleanest, smartest, most efficient, and trustworthy content to our users. Our data teams are vital to making data-informed decisions, engaging our audiences, creating data products, and staying competitive in the digital age. The data teams at Axios directly impact revenue, strategic decisions, and products across the company at large.

Directly manages data engineering leadership and some engineering directs through 1:1s, coaching, and feedback as well as takes ownership for all administrative functions
Owns and is responsible 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, with strong focus on company goals
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 to initiatives
Partners with key stakeholders, most often in the realm of legal compliance
Defines and owns product health metrics with input from Data Leadership
Provides technical guidance, staying informed on industry best practices, and emerging technologies in all relevant areas
Partners across the engineering department to assure alignment with standards, vision, and engineering culture
Supports cross-functional teams to work productively, with effective prioritization and resourcing
Owns technical relationships with relevant key vendors and supports the contract review and vendor selection process
Hires, onboards, manages, and supports a diverse team of individual contributors while actively fostering an inclusive environment
Maintains a culture that balances healthy urgency with the need for downtime and recuperation

10+ years of experience leading data-focused engineering teams, with some of that time managing managers
5+ years of data science machine learning experience
Experience working with stakeholders at an executive level
An expert grasp of data engineering including skills in data architecture design, data pipeline development, data modeling, data quality, and governance
Skilled in working hands-on with columnar data warehouses, business intelligence tools, and the Python ecosystem
Understanding of modern ML infrastructure and tooling to support data initiatives.
Knowledge of applicable principles, methodologies, and tools in the data engineering analytics field
A track record of approaching management with a human-first mindset, while maintaining a healthy sense of urgency on deliverables
Excellent listening and communication skills that translate well to a remote work environment