VP of Data at KAYAK managing data engineering and data science teams to improve analytics and ML solutions. Leading data strategy and platform development to enhance decision-making and business impact.
Responsibilities
Define and drive the company’s data strategy and roadmap to enable analytics, experimentation, and machine learning aligned to business goals.
Lead design, development, and evolution of the data platform (ingestion, processing, storage, catalogs, APIs) to ensure scalability, reliability, and performance.
Oversee data science teams to deliver predictive models, experimentation frameworks, and ML systems that create measurable business impact.
Establish and enforce data governance, metadata management, lineage, and data quality standards to ensure trust and compliance.
Partner closely with DevOps, Cloud/Infrastructure, Engineering, Product, and Security to productionize data products, define SLAs, and align on deployment and monitoring practices—collaborating with but not directly managing DevOps teams.
Recruit, mentor, and grow high-performing data engineering and data science teams; define org structure, career paths, and performance metrics.
Define KPIs for data platform adoption, model performance, data quality, and time-to-insight; use outcomes to prioritize investments.
Guide architecture choices (cloud-native data stacks, streaming vs batch, data warehouse vs data lakehouse), review critical designs, and promote best practices in engineering and ML ops.
Requirements
Experience: 10+ years building data platforms and analytics/ML organizations, with at least 5 years in senior leadership.
Technical depth: Strong background in modern data engineering and data science practices (ETL/ELT, data modeling, warehousing/lakehouse, streaming, feature stores, ML lifecycle). Familiarity with cloud platforms (AWS/Azure/GCP) and CI/CD for data/ML workflows.
Leadership: Proven track record hiring, scaling, and developing technical teams and partnering across product and engineering organizations.
Governance & security: Experience implementing data governance, privacy controls, access management, and compliance processes.
Communication & business impact: Able to translate technical tradeoffs into business value and influence senior stakeholders.
Education: Degree in CS, engineering, statistics, or related field (or equivalent experience).
Benefits
Work from (almost) anywhere for up to 20 days per year
Flexible hours and ability to work from home 1 or 2 days per week
Generous retirement plans
Awesome health, dental and vision insurance plans with flexible spending accounts
Focus on mental health and well-being:
Company-paid therapy sessions through SpringHealth
Company-paid subscription to HeadSpace
Company-wide week off a year - the whole team fully recharges (and returns without a pile-up of work!)
No meeting Fridays
Universal paid parental leave
Generous paid vacation + time off for your birthday
Paid volunteer time
Focus on your career growth:
Development Dollars
Leadership development
Access to thousands of on-demand e-learnings
Travel Discounts
Employee Resource Groups
Competitive retirement and health plans
Free lunch 2 days per week
Fun quarterly events such as boat trips, arcades, ski trips, Thursday happy hours, and more
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