Airalo
Analytics Engineering Manager
Vaga remota de Analytics Engineering com fit claro de localização do candidato.
Publicada4 de jul. de 2026
Países elegíveis2 países aceitos
Sinal de senioridadeLead
Modelo de trabalhoRemoto
Locais aceitos para candidatos
EspanhaReino Unido
Resumo da vaga
Analytics Engineering Manager
Requisitos e responsabilidades
Conteúdo da vaga extraído em seções para revisão mais rápida.
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 haves
- 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 haves
- 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
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