Analytics Engineering Manager

This role combines technical expertise with business impact, whether it’s building robust data pipelines or directly solving business problems and delivering insights. As the leader of the analytics engineering team, you’re going to: Build and lead the team: Hire, mentor, and grow a team of analytics engineers who will work closely with product and data science teams. Develop deep product expertise: Ensure your team deeply understands product data, building targeted data marts and tools that solve real business problems. Leverage AI and LLMs: Investigate how LLMs and AI can change analytics and build data foundations that support these future needs. Focus on creating data marts optimized for LLMs and AI-driven analytics. Unlock the value of our data: Partner with stakeholders to maximize the commercial impact of data by building scalable models, optimizing pipelines, and integrating cross-product data for better decision-making. Directly deliver business impact: Oversee the creation of dashboards, ad-hoc analytics, and self-service tools that empower product teams to make data-driven decisions. Prioritize outcomes over tools: Leverage the right frameworks and technologies to drive value, whether by developing abstractions, creating internal data apps, or improving scalable workflows. Bridge the gap between business and data: Liaise between product data science, product managers, and central data engineering. Ensure your team uses central data tools and infrastructure while remaining agile and product-focused.