Top Data Analyst Jobs in Spain

Build and maintain reliable datasets, data models, SQL transformations, and analytical assets. Translate business requirements into documented data solutions, validate outputs, and collaborate with stakeholders, product managers, and data teams. The role involves using AI tools responsibly, contributing to data best practices, and developing toward autonomous ownership of data products.

Analyze player behavior and business performance across user acquisition, retention, and monetization. Build reliable data models, pipelines, Power BI dashboards, and reports using modern data tools. Support A/B testing, predictive analytics, behavioral segmentation, machine learning, and Generative AI initiatives. Communicate actionable insights to stakeholders, maintain analytical code in GitLab, troubleshoot data issues, and promote best practices across the organization.

Analyzes and validates consumer panel data, executes data operations, investigates anomalies, resolves data-quality issues, and monitors quality metrics. The role collaborates with Operations, Client Operations, Data Science, and Project Management teams to improve processes, standardize methodologies, document findings, and support country-specific projects. It requires SQL, data analysis, strong problem-solving skills, fluent English plus Spanish or Portuguese, and availability in Madrid.

Executes sample data operations, monitors data quality, investigates anomalies, resolves data-related queries, and supports country-specific projects. The role collaborates with Operations, Data Science, Client Operations, and Project Management teams to improve processes, standardize practices, document findings, and enhance operational performance. Candidates need data analysis experience, SQL knowledge, strong analytical skills, fluent English plus Spanish or Portuguese, and must be based in Madrid.

Build end-to-end compliance analytics and data infrastructure for KYC/KYB funnels, remediation campaigns, and financial exposure. Model and transform data with dbt and Omni, create self-service dashboards for product, ops, risk and compliance, and measure campaign impact to drive operational decisions.

Own end-to-end analytics for subscription products and web funnels, including KPI definition, dashboards, funnel and cohort analysis, payment performance, user behavior, experimentation, and anomaly monitoring. Build reliable SQL data models and maintain event taxonomies and tracking. Partner cross-functionally with Product, Marketing, Engineering, Finance, and BI to improve conversion, retention, revenue, and LTV. Mentor analysts and communicate actionable recommendations to stakeholders.

Lead global SEM analytics for Rover, guiding bidding and investment decisions through spend allocation, incrementality testing, attribution, experimentation, and customer-value analysis. Diagnose acquisition performance, build trusted dashboards, shape the analytics roadmap, and partner with Finance, Data Science, and Engineering. The role also mentors analysts, reviews analytical work, and translates complex findings into strategic recommendations across brands and markets.

Analyze auction-level and campaign data, monitor A/B tests, and identify performance patterns across advertisers and segments. Build scalable dashboards and reporting frameworks using Looker or Tableau, automate analysis with SQL and Python, and translate machine-learning model changes into business impact across CPI, CPA, and ROAS. Partner with Data Science and ML teams to validate results, identify data-quality issues, and provide proactive business recommendations.

Analyze and model supply chain data across ERP and APS systems, manage data quality and governance, support data architecture and integration, and create dashboards that inform transformation projects. Collaborate with business, IT, and client teams to gather requirements, communicate insights, and improve master data practices. The role involves global client projects, workshops, and travel while remaining hands-on with data querying, validation, modeling, and visualization.

Leads research and advisory work for CIOs on data, analytics, and AI strategy, governance, operating models, architecture, value realization, and emerging technologies. Develops thought leadership, market analysis, presentations, and actionable client guidance; evaluates agentic and composite AI, modern data platforms, AI-ready data, organizational maturity, and capability-building needs. Represents Gartner at client meetings and conferences, supports sales, mentors colleagues, and shapes research agendas.

Own end-to-end product and marketing analytics for subscription products and web funnels. Define KPIs, build trusted dashboards and reusable SQL data models, analyze funnels, cohorts, retention, LTV, churn, and user behavior, and identify optimization opportunities. Maintain event tracking and taxonomy, monitor anomalies, communicate insights to stakeholders, and mentor junior and mid-level analysts. Collaborate cross-functionally with Product, Marketing, Data Engineering, and BI teams to support experimentation and data-driven decisions.

Analyze large-scale user and product data, design and evaluate A/B tests, define and validate product and business metrics, build dashboards and reports, and partner with engineers, data scientists, product, and customers to translate insights into product improvements.

Analyzes Growth and marketing performance data, defines metrics and data models, investigates data quality issues, and delivers actionable recommendations. Leads analytical projects from scoping through communication, builds scalable reporting solutions, partners with Data Engineering and Data Science, and supports experimentation and investment decisions. The role also mentors analysts and communicates findings to technical teams, business partners, and senior leadership.

Develop and maintain business intelligence dashboards and analyses supporting regional decisions across Sales, Operations, Finance, and Supply Chain. Translate business requirements into actionable insights, manage analytics projects, improve data quality, document data models, support BI governance, train users, and identify automation opportunities. The role partners with business and technical stakeholders across multiple countries and platforms.

Processes and validates managed investment data across global markets, ensuring accuracy, completeness, and timely delivery. Collaborates with global teams, fund companies, and internal clients; manages data issues, acquisition channels, specifications, and user stories. The role also improves procedures, develops analytical tools, documents use cases, and supports process improvement initiatives using Lean Six Sigma methodologies.

Supports technology change initiatives by documenting impacts, coordinating readiness and adoption activities, tracking engagement metrics, creating communications and learning content, managing change champion communities, and maintaining SharePoint and Viva Engage content. The role partners with PMO, project managers, technology leaders, and Corporate Communications to improve adoption of tools, platforms, and services across a global organization.

Lead marketing analytics initiatives, including statistical evaluation of campaign performance, predictive modeling, LTV and incrementality analysis, data pipeline development, and interactive visualization. Partner with marketing and cross-functional teams to identify growth opportunities, communicate actionable insights to senior stakeholders, and prototype AI-driven automation for recurring analytics workflows.

Leads a team of 3–5 data analysts, prioritizes analytical work, and analyzes large real-time bidding datasets to identify market trends and revenue opportunities. Builds self-service BI and automated reporting frameworks, establishes data quality and documentation standards, and partners with Product, Data Science, and Engineering to guide product decisions.

Owns sales analytics products, dashboards, KPI frameworks, datasets, and data marts supporting commercial decisions across European markets. Identifies growth opportunities through analysis of sales, pricing, promotions, customer behavior, and market trends. Leads cross-functional analytical projects, improves self-service analytics using automation and AI, and communicates actionable recommendations to senior stakeholders.

As a Data Analyst, you'll analyze user behavior and product performance, creating reports and dashboards to drive business insights. You'll collaborate with cross-functional teams and utilize SQL, Python, and data visualization tools to enhance user experiences and define key performance indicators.

Analyze and model data to support transaction monitoring and FinCrime investigations. Own end-to-end delivery of analytics solutions, build dashboards, ensure data quality and auditability, support regulatory reporting and automate FinCrime processes.

As a Fraud Data Analyst, you will architect real-time defense strategies against payment fraud, develop precision rules, optimize decisioning stacks, and report performance metrics to senior leadership while ensuring a frictionless user experience.

Build production-grade finance data products: design dbt models on Redshift, create Metabase self-service dashboards, validate reconciliations and provisioning, partner with Finance to ensure auditable, single-source-of-truth metrics, and drive data governance and quality improvements.

The Senior Data Analyst will provide product, operations, and business analytics; analyze internal, market, and customer data; translate findings into actionable insights; improve product features; define data models; ensure data quality; and build dashboards and analytical models using Snowflake, Looker, Amplitude, and related tools. The role also involves A/B testing, causal inference, stakeholder communication, and collaboration with data engineers.

Join the global data team to collect, validate, and maintain investment data (Morningstar). Manage provider relationships, meet production deadlines, resolve data tickets, document processes, and drive process improvements using project management methodologies to ensure high data quality and client-focused delivery.