Analytics Engineering Manager
Airalo · Spain
- Hybrid
- Full-time
- $150,000 / year
- Spain
Job highlights
- Lead analytics engineers and build data infrastructure.
- Establish self-service analytics and data modeling practices.
- Own core data models, semantic layer, and reporting.
- Partner with stakeholders to meet analytical needs.
- Drive adoption of Lightdash for business reporting.
About the role
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: https://airalo-public.notion.site/airalo-public-handbook
About You
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.
About The Role
Position: Full-time / Employee
Location: Remote-first
Benefits: Health Insurance, work-from-anywhere stipend, annual wellness & learning credits, annual all-expenses-paid company retreat in a gorgeous destination & other benefits
We're looking for an Analytics Engineering Manager to lead our self-service analytics infrastructure and data modeling practice at Airalo. You'll own the foundations that make analytics possible at scale: the semantic layer, core data models, dashboards, and the self-service platform (Lightdash) that enables teams across the business to answer their own questions. This is a building role-you'll establish how we model data, how we govern metrics, and how we roll out self-service capabilities across a 20M+ user business operating in 190+ countries.
You'll report to the Director of Data and partner closely with analytics teams and stakeholders across the business, translating their analytical needs into scalable, production-quality data models. Success looks like business users confidently answering their own questions, a governed semantic layer that analytics teams trust, and a self-service platform that replaces our patchwork of legacy reporting tools and robust data models that scale without use cases.
What You'll Do
- 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
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
- 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, MetricFlow, 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 deliver real impact, and you prioritise 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
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
Background Checks & Equal Opportunity
By applying, you acknowledge and agree that, in case of successful application, Airalo may request to run background checks as a condition for entering into an agreement with you. Rest assured that these checks will only occur upon your prior consent and at the end of the selection process, and will be strictly limited to what is allowed under the laws that are applicable to you. All data that you share or that we collect in connection with such checks will be processed in accordance with our Privacy Policy, available here: https://www.airalo.com/more-info/privacy-policy?srsltid=AfmBOooBT0rXAj1FaNelZ3VfN0wvhwzvAoxdtHnOKSVETpiSjiXVuycy
We sincerely thank all applicants in advance for submitting their interest in this opportunity. Airalo is an equal-opportunity employer and values diversity, equity & inclusion. We do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We are committed to providing reasonable accommodations upon request for individuals with disabilities throughout our job interview process.
At Airalo, we use AI-assisted tools as part of our recruitment process. Your application will be reviewed using tools that help our recruiters analyze and organize CV information. These tools support, but do not replace, human judgment; all hiring decisions are made by humans. If you progress to an interview, we may use tools to generate AI-assisted notes - you can opt out of these. For more information on how we handle your data, see our Privacy Policy: https://www.airalo.com/more-info/privacy-policy.
Key skills/competency
- Analytics Engineering
- Data Modeling
- Team Leadership
- dbt
- SQL
- Python
- Semantic Layer
- Self-Service Analytics
- Data Governance
- Business Acumen
Skills & topics
- Analytics Engineering Manager
- Analytics Engineering
- Data Modeling
- Team Leadership
- dbt
- SQL
- Python
- Semantic Layer
- Self-Service Analytics
- Data Governance
- Business Acumen
- Full-time
- Remote
How to get hired
- Tailor your resume: Highlight your analytics engineering, data engineering, and people management experience, emphasizing dbt and self-service analytics adoption.
- Showcase leadership: Detail your experience building or scaling teams and driving data strategy in ambiguous environments.
- Demonstrate technical skills: Clearly list your proficiency in SQL, Python, dbt, and semantic layer tools like Lightdash or Looker.
- Emphasize business impact: Articulate how your data products and initiatives have delivered tangible business value and user adoption.
- Prepare for culture fit: Research Airalo's values and be ready to discuss your approach to collaboration, honesty, and continuous learning.
Technical preparation
Behavioral questions
Frequently asked questions
- What is the work arrangement for the Analytics Engineering Manager role at Airalo?
- This Analytics Engineering Manager position at Airalo is a remote-first role, offering flexibility for candidates to work from anywhere.
- What are the key responsibilities of the Analytics Engineering Manager at Airalo?
- The Analytics Engineering Manager at Airalo will lead a team of analytics engineers, establish self-service analytics infrastructure, own core data models and the semantic layer, and drive the adoption of Lightdash for business reporting.
- What technical skills are essential for the Analytics Engineering Manager role at Airalo?
- Essential technical skills for this role include deep proficiency in dbt, strong SQL, experience with Python, and experience with semantic layer tools like Lightdash or Looker. Familiarity with dimensional modeling and data warehouse design is also crucial.
- What kind of team will I be managing as an Analytics Engineering Manager at Airalo?
- As the Analytics Engineering Manager at Airalo, you will lead and grow a team of analytics engineers, currently numbering two and planned to scale to four this year, fostering a culture of craft, documentation, and user empathy.
- What is Airalo's stance on diversity and inclusion for the Analytics Engineering Manager position?
- Airalo is an equal-opportunity employer that values diversity, equity, and inclusion. They do not discriminate based on race, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
- How does Airalo use AI in its recruitment process for the Analytics Engineering Manager role?
- Airalo utilizes AI-assisted tools to help recruiters analyze and organize CV information for the Analytics Engineering Manager role. These tools support human judgment, and all hiring decisions are made by humans. AI-assisted notes may be used during interviews, with an option to opt-out.
- What makes the Analytics Engineering Manager role at Airalo a 'building role'?
- This Analytics Engineering Manager role at Airalo is considered a 'building role' because you will be establishing how data is modeled, how metrics are governed, and how self-service capabilities are rolled out across a large user base and multiple countries.
- What are the benefits offered for the Analytics Engineering Manager position at Airalo?