Analytics Engineering Manager

About Airalo

Alo! Airalo is the world’s first eSIM store that helps people connect in over 200+ countries and regions across the globe. We are building the next digital service that revolutionizes the telecom industry. We are a travel-tech company and an equal-opportunity environment that values and executes diversity, inclusion, and equity. Our team is spread across 50+ countries and six continents. What glues us together is our commitment to changing the way you connect.

Check out more information about Airalo in our Public Handbook: (Use the "Apply for this Job" box below).-handbook

We hope that you care deeply about the quality of your work, the intrinsic worth of tasks, and the success of your team. You are self-disciplined and do not require micromanagement in terms of your skillset and work ethic. You do your best to flourish as an individual every day while working hard to foster a collaborative team environment. You believe in the importance of being — and staying — authentic, honest, positive, and kind.

You are a good interlocutor with clear and concise communication. You are able to manage multiple projects, have an analytical mind, pay keen attention to detail, and love to get your hands dirty. You are cognizant, tolerant, and welcoming of vulnerabilities and cultural differences.

Full-time / Employee

Remote-first

• Health Insurance
• Work-from-anywhere stipend
• Annual wellness & learning credits
• Annual all-expenses-paid company retreat in a gorgeous destination & other benefits

• Lead and grow a team of analytics engineers (currently 2, scaling to 4 this year), building a culture of craft, documentation, and user empathy
• Drive the rollout and adoption of Lightdash as our single source of truth for business reporting, based on a unified KPI framework currently in progress
• Own all dashboard development initially - from executive reporting to operational views, with support from analysts - then fully transition the ownership to analysts as self-service matures, building the templates and processes that enable this shift
• Partner with stakeholders to translate reporting needs into well-designed, maintainable data products
• Design and deliver training and enablement programs for business users across all functions
• Own and evolve our core dbt models and semantic layer to support key analytical use cases: customer LTV, acquisition effectiveness retention, funnel performance, and financial reporting
• Establish governance and standards: metric definitions, dashboard design patterns, modeling practices, testing frameworks, and documentation
• Partner with analysts to translate their needs into scalable data assets, and with Data Engineering on pipeline reliability and data quality
• Partner with Data Engineering on pipeline reliability, data quality, and infrastructure decisions
• Balance rigour with delivery speed - we're still building foundations while the business moves fast

• 5+ years in analytics engineering, data engineering, or technical analytics roles, with 2+ years of people management experience - ideally building or scaling a team
• You're a hands-on leader who partners with senior leadership on strategy and priorities while owning execution and day-to-day team decisions.
• Deep proficiency in dbt - you've built and scaled dbt projects, not just contributed to them.
• Strong SQL and experience with at least one programming language (Python preferred).
• Experience implementing or heavily using a semantic layer / metrics layer (Lightdash, Looker, Metric Flow, or similar).
• Track record of driving self-service analytics adoption - training programs, documentation, stakeholder enablement.
• Familiarity with dimensional modeling, data warehouse design patterns, and data quality frameworks.
• Experience working closely with analysts and translating their needs into scalable data models.
• Strong business acumen - you're driven to build scalable data products that real impact, and you prioritize ruthlessly to get there.
• Comfortable with ambiguity and greenfield data environments, with a passion for building team culture and raising the bar on data quality and usability.