Analytics Lead

The Role We are seeking a highly skilled and experiencedAnalytics Leadto join our technology and product teams in Málaga. In this role, you will take a leading part in defining the company’s analytics strategy, building frameworks for measuring product and customer performance, and providing actionable insights that drive business growth. This is a hands-on position with a strong focus on technical leadership, mentoring, and shaping how data informs decision-making across our global teams.Who We Are At Liquid Barcodes, we’ve developed the world’s most advanced digital loyalty and subscription platform, helping our clients connect with customers and build lasting loyalty. Our technology transforms digital marketing in the convenience sector by closing the loop between the customer and the store—delivering measurable impact on engagement, basket size, and retention. We work with leading retail brands such as 7-Eleven, Circle K, and Cepsa. Headquartered in Norway, we also have offices in Spain and the US. Our Málaga hub, located in the city center opposite the Cathedral, serves as a key innovation and operations center for our growing international business.Key Responsibilities Analytics Foundations & Strategy Define analytical requirements for core customer use cases (loyalty mechanics, campaign performance, app engagement, subscriptions, etc.). Establish KPI frameworks and structured metric definitions used across the company. Own documentation, governance, and consistency of analytics standards.Hands-On Data Exploration & Prototyping Use SQL and a general-purpose programming language (Python, R, Julia, etc.) to explore customer and product data, validate patterns, generate insights, and build analytical prototypes. Conduct deep analyses on user behavior, loyalty performance, program effectiveness, segmentation, and customer lifecycle trends. Create lightweight models or indicators (e.g., engagement scores, churn signals) for internal consumption.Data Modeling & Warehouse Collaboration Work closely with the Lead Data Engineer to design and refine data models and transformations. Validate the warehouse structure to ensure it supports customer use cases and analytics requirements. Contribute to the evolution of our data platform approach (e.g., GCP/BigQuery), ensuring analytics needs are natively supported.Reporting & Visualization Build reports and dashboards to help Customer Success, Product, Onboarding/PM, and Executives understand customer performance and product usage. Enable self-serve analytics through clear documentation and structured metric layers. Ensure reporting is trusted, consistent, and actionable across teams.AI-Assisted Analytics Use AI tools to accelerate insight generation, automate reporting, and surface trends faster. Explore AI-enhanced capabilities such as summarization, anomaly detection, and natural language querying. Support future internal AI copilots or assistant features in collaboration with engineering.Quality, Governance & Requests Define data validation rules and documentation standards. Prioritize and manage ad-hoc data requests with clarity and structure.What We’re Looking ForRequired 5+ years in data analytics, product analytics, or BI within a SaaS or digital environment. Strong SQL and experience with modern data warehouses (BigQuery, Snowflake, Redshift, etc.). Ability to write code in a general-purpose language for exploration, automation, and prototyping. Experience defining KPIs, reporting structures, and analytics requirements from scratch. Proficiency building dashboards and reports with modern BI tools (Looker, Tableau, Power BI, Metabase, etc.). Strong communication skills and ability to translate data into recommendations. A builder mindset and comfort working in a zero-to-one environment.Nice to Have Hands-on experience with Google Analytics (or similar web/app analytics tools). Experience with dbt or modern transformation frameworks. Exposure to consumer engagement, CRM, mobile apps, or loyalty analytics. Experience using AI tools for analytics or reporting. Familiarity with experimentation or A/B testing. Direct experience with BigQuery (especially relevant if we go with a GCP-based data platform).What’s in it for you?