Analytics Engineering Manager
Team: Data Analytics
Location: Spain, United Kingdom
Commitment: Full-Time
Workplace Type: remote
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
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