Analytics Engineering Manager

About Airalo

Alo! Airalo is the world’s first eSIM store, connecting people in over 200+ countries and regions globally. We are revolutionizing the telecom industry as a travel-tech company committed to diversity, inclusion, and equity. Our team operates across 50+ countries and six continents, united by our mission to change how you connect.

About You

We are seeking an individual who prioritizes quality work, intrinsic task worth, and team success. You are self-disciplined, requiring no micromanagement, and strive for individual growth while fostering a collaborative environment. Authenticity, honesty, positivity, and kindness are core to your interactions. You communicate clearly and concisely, manage multiple projects, possess an analytical mind, pay keen attention to detail, and enjoy hands-on work. You are also cognizant, tolerant, and welcoming of vulnerabilities and cultural differences.

About The Role

This is a Full-time / Employee, remote-first position. Airalo offers benefits including Health Insurance, a work-from-anywhere stipend, annual wellness & learning credits, and annual all-expenses-paid company retreats in gorgeous destinations.

We are looking for an Analytics Engineering Manager to lead our self-service analytics infrastructure and data modeling practice at Airalo. You will own the foundational elements enabling analytics at scale: the semantic layer, core data models, dashboards, and the self-service platform (Lightdash). This is a building role, where you will establish data modeling methodologies, metric governance, and self-service capabilities for a business with 20M+ users across 190+ countries.

Reporting to the Director of Data, you will collaborate closely with analytics teams and stakeholders, translating analytical needs into scalable, production-quality data models. Success is defined by confident business users, a trusted semantic layer, and a self-service platform that replaces legacy reporting tools, along with robust, scalable data models.

What You'll Do

• Lead and grow a team of analytics engineers (currently 2, scaling to 4 this year), cultivating 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.
• Own all dashboard development initially, from executive reporting to operational views, then transition ownership to analysts as self-service matures, building necessary templates and processes.
• 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 such as customer LTV, acquisition effectiveness, retention, funnel performance, and financial reporting.
• Establish governance and standards for 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, data quality, and infrastructure decisions.
• Balance rigor with delivery speed, building foundations while adapting to the fast pace of business.

Must Have

• 5+ years in analytics engineering, data engineering, or technical analytics roles, with 2+ years of people management experience, ideally building or scaling a team.
• 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, having built and scaled dbt projects.
• Strong SQL skills and experience with at least one programming language (Python preferred).
• Experience implementing or heavily using a semantic layer / metrics layer (Lightdash, Looker, MetricFlow, or similar).
• Track record of driving self-service analytics adoption through training programs, documentation, and 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, driven to build scalable data products that deliver real impact, with ruthless prioritization skills.
• Comfortable with ambiguity and greenfield data environments, with a passion for building team culture and raising data quality and usability.

Nice to Have

• Experience in marketplace, B2C, or subscription/usage-based businesses.
• Previous work in low-maturity or greenfield data environments.
• Familiarity with our stack: dbt, BigQuery, Lightdash, Fivetran.
• Experience with marketing analytics use cases: attribution, LTV, cohort analysis.
• Previous experience at a scale-up that went through hypergrowth.

Key skills/competency

• Analytics Engineering
• Data Modeling
• dbt
• SQL
• Python
• Semantic Layer (Lightdash)
• Data Governance
• Self-service Analytics
• Team Leadership
• BigQuery