About the job
At Intercom, we are dedicated to revolutionizing customer service through advanced AI technology. Our flagship AI agent, Fin, empowers businesses to provide exceptional, round-the-clock customer support, enhancing overall customer experiences. When paired with our Helpdesk, Fin evolves into the complete Intercom Customer Service Suite, facilitating AI-enhanced assistance for complex inquiries requiring human intervention.
Founded in 2011 and trusted by nearly 30,000 businesses worldwide, Intercom is at the forefront of setting new benchmarks for customer engagement. Guided by our core values, we continually strive to innovate, deliver with urgency, and provide unparalleled value to our clientele.
What’s the Opportunity?
The Analytics Engineering team is pivotal in delivering precise and current data tables that underpin Intercom’s crucial operational and strategic decisions.
Utilizing their extensive understanding of Go-To-Market (GTM) teams, the team anticipates data requirements, employing their technical expertise to craft effective data models and transform them into high-quality data assets within our data warehouse. They excel in optimizing data models and addressing data quality issues at their core.
This team acts as the connective tissue between our Analyst teams and Data Infrastructure teams, ensuring streamlined communication and enhanced efficiency.
What Will I Be Doing?
- Data Platform Development: Design, construct, and oversee scalable data pipelines and ELT processes to establish a robust, analytics-ready data platform.
- Cross-functional Collaboration: Collaborate with engineering, analytics, and business teams to grasp data needs and deliver accurate and insightful data solutions.
- Data Strategy & Governance: Spearhead initiatives in data model development, data quality ownership, warehouse management, and production support for essential workflows.
- Advanced Analytics & Insights: Conduct comprehensive data analyses and develop customized models to inform strategic business decisions and performance assessments.
- Automation & Optimization: Enhance data collection and reporting processes to minimize manual tasks and boost efficiency.
- Innovation in Data Infrastructure: Develop scalable solutions...

