Senior Analytics Engineer

The role

You will design and build trusted data models across Lighthouse's commercial and financial domains — modeling deals, accounts, and opportunities for go-to-market teams, and supporting revenue, retention, and churn analysis for finance — while owning delivery end-to-end from requirements through implementation and documentation, using AI tools responsibly to accelerate your work while remaining accountable for output quality, and collaborating closely with commercial, finance, and analytics stakeholders.

What we expect

• You have senior-level experience in analytics engineering, data warehousing, or a closely related role and can operate independently with limited overlap across time zones.
• You have strong SQL skills and hands-on experience building robust, understandable data models.
• You have practical experience with dbt or another data transformation tool.
• You understand core data warehousing principles and can architect models across commercial and financial domains.
• You can gather requirements, perform functional analysis, and translate stakeholder questions into technical solutions.
• You can work directly with both technical and non-technical leaders, adapting your communication to be concise and clear.
• You have basic Python scripting skills or can critically review scripts produced with artificial intelligence assistance.
• You use AI effectively and thoughtfully: You use AI in your day-to-day as a supporting and enhancing tool during development, review, documentation and presentation processes. In doing so, you question outputs, handle data with care and always remain accountable for your work. You understand the capabilities and limitation of your AI tools and can provide clear and structured feedback on them.
• You understand how reliable data foundations support agentic frameworks, retrieval-augmented generation, or conversational analytics, even if you have not built those systems yourself.
• You are comfortable supporting colleagues and explaining technical needs across teams without needing to formally manage them.