Responsibilities
- Guide and expand a team of analytics engineers, fostering a culture focused on craftsmanship, thorough documentation, and user empathy.
- Champion the implementation and widespread use of Lightdash as the unified source for business reporting, aligned with an ongoing KPI framework.
- Initially take charge of all dashboard creation, from executive summaries to operational insights, with analyst assistance, and later transfer full ownership to analysts as self-service capabilities advance, developing templates and processes to facilitate this transition.
- Collaborate with stakeholders to convert reporting requirements into well-structured, sustainable data products.
- Create and execute training and empowerment initiatives for business users across various departments.
- Manage and enhance core dbt models and semantic layers to aid critical analytical areas: customer lifetime value, acquisition efficiency, retention rates, funnel performance, and financial reporting.
- Set up governance and standards covering metric definitions, dashboard design approaches, modeling techniques, testing protocols, and documentation practices.
- Work with analysts to turn their requirements into scalable data resources and collaborate with Data Engineering on pipeline stability and data integrity.
- Partner with Data Engineering on ensuring pipeline reliability, data quality, and infrastructure choices.
- Maintain a balance between thoroughness and rapid delivery, as foundational systems are established amid fast-paced business operations.
Requirements
- Minimum of five years in analytics engineering, data engineering, or technically focused analytics positions.
- At least two years of experience in people management, preferably involving team building or expansion.
- Hands-on leadership approach, collaborating with senior executives on strategy and focus areas while overseeing execution and daily team decisions.
- Advanced expertise in dbt, with a background in developing and scaling dbt projects beyond mere contributions.
- Proficient in SQL and knowledgeable in at least one programming language, with a preference for Python.
- Background in implementing or extensively utilizing a semantic or metrics layer such as Lightdash, Looker, MetricFlow, or comparable tools.
- Proven ability to promote self-service analytics adoption through training initiatives, documentation, and stakeholder support.
- Understanding of dimensional modeling, data warehouse design principles, and data quality frameworks.
- Experience in close collaboration with analysts to convert their needs into scalable data models.
- Strong business insight, motivated to create scalable data products that yield tangible results and adept at prioritizing effectively to achieve goals.
- Comfort with uncertainty and new data environments, coupled with enthusiasm for fostering team culture and enhancing data quality and usability standards.
Nice to Have
- Background in marketplace, business-to-consumer, or subscription/usage-based companies.
- Previous involvement in low-maturity or newly established data settings.
- Familiarity with the technology stack including dbt, BigQuery, Lightdash, and Fivetran.
- Experience with marketing analytics applications such as attribution, lifetime value calculations, and cohort analysis.
- History at a scaling company that experienced rapid growth phases.
Benefits
- Details on benefits available at the provided link: https://airalo-public.notion.site/Benefits-25396a97ffca81fb9bc1f0be479f1be3?pvs=74
Work Arrangement
Remote (Worldwide) — Spain, UK
Other
- English serves as the primary working language for daily communication, requiring comfort in both spoken meetings and written asynchronous exchanges.
- Contract terms: In Spain, full-time permanent contrato indefinido facilitated through Deel as the employer of record; in the UK, full-time permanent position.
- Applicants acknowledge that, upon successful application, background checks may be requested as a condition for agreement, conducted only with prior consent at the selection process end and limited to legally permissible scope under applicable laws.
