Senior Engineering Manager, Central Data Products

Lead the vision, strategy, and execution of a portfolio of data and ML products used across the company. Your team is senior and cross-functional (Data Scientists, MLOps Engineers, and a Product Manager), and its output is measured in company-level business impact, not in models shipped.

What you'll do

• Lead all hiring and performance management processes for your team, helping Data Scientists and MLOps Engineers reach their full potential in a domain that mixes classical ML, LLMs, and production data infrastructure.
• Drive high-impact outcomes by managing the team's roadmap and portfolio allocation across a diverse set of horizontal data products, making explicit trade-offs between exploration, productionalization, and ongoing operations.
• Find and deliver solutions to complex technical challenges that span multiple services and business domains, from marketplace tagging quality to predictive customer models.
• Own adoption, not just delivery. Horizontal data products only create value when clusters build on them, so you will drive operationalization together with Growth, Supply, and Consumer stakeholders.
• Raise the operational bar for data products in production: quality baselines, LLM-as-judge and golden dataset monitoring, incident management, and reliable at-scale pipelines.
• Build strategic partnerships with senior stakeholders across Product, Engineering, Marketing, and Sales, aligning ownership of shared systems from day one.

What you'll need

• A strong sense of ownership, ensuring technical and product plans are aligned with stakeholders, team, and organizational goals.
• Ability to approach ambiguous, broadly scoped problems with an open mind and a bias toward a directional first version over extended discovery.
• Strong technical background in machine learning and engineering, enabling you to evaluate decisions on modeling approaches, data architecture, evaluation methods, and production pipelines.
• Active leadership in technical, design, and product discussions, balancing exploration speed with production reliability.
• Passion for building and developing a high-performing team: mentoring, coaching, and empowering senior individual contributors.
• Ability to translate technical results into business decisions and hold your own with commercial stakeholders on impact, trade-offs, and prioritization.
• Excellent written and verbal communication skills in English.

Nice to have

• Experience leading teams that own horizontal or platform-like data products serving multiple internal customers, where adoption is as hard as the build.
• Experience running ML or data products in production, including quality monitoring, evaluation systems, and incident management.
• Experience applying LLMs to large-scale classification, extraction, or tagging problems, and knowing when a classical model is the better answer.
• Experience in a high-growth environment, taking projects from zero to one and scaling them across an organization.

What they offer

• Annual personal growth budget and mentorship programs
• Work from anywhere in the world for 30 days per year
• Hybrid working approach with three days in office collaboration and two days optional at home focus time
• Monthly transportation and fitness budget
• Health and wellness benefits
• Discounts on GetYourGuide activities for you, friends, and family