Top Data Analyst Jobs in Spain

Analyze large-scale security telemetry, threat intelligence, endpoint, and detection data to identify trends, anomalies, and emerging threats. Build dashboards, reports, data pipelines, and KPI frameworks using SQL, Python, LogScale, or similar tools. Collaborate with data engineering, product, and engineering teams to ensure data quality and translate complex findings into actionable insights for technical and non-technical stakeholders.

Collects, maintains, and validates portfolio data across global markets, ensuring accuracy, completeness, coverage, and timely delivery. Collaborates with global data teams, fund companies, clients, and third-party providers. Improves procedures through analytical tools, automation, Lean Six Sigma, and process-improvement projects. Provides expertise on investment data calculations, supports portfolio template testing, handles data transfer agreements, and monitors relevant financial regulations.

The Data Analyst will analyze data from multiple sources to generate business insights and support strategic decision-making. Responsibilities include developing metrics, dashboards, experiments, analyses, data frameworks, and behavioral insights in collaboration with analysts, engineers, and data scientists. The role requires strong SQL expertise, statistical analysis using Python or R, Looker experience, data storytelling, and stakeholder management skills.

Support global data team collecting, organizing, and verifying financial data across markets. Assist with acquisition channels, resolve data issues, document client requests, and apply project management practices (LEAN Six Sigma) to improve workflows and meet production deadlines.

Contribute to the Tech team by analyzing data to inform product roadmap and prioritization, interact with clients and internal teams to understand needs, make data-driven decisions, and lead development ownership of impactful features.

Analyze user behavior, product funnels, experiments, and monetization across subscription-based mobile apps. Own product metrics including activation, retention, conversion, LTV, and CAC; build dashboards and reports; identify opportunities and root causes; and translate data into recommendations for product roadmaps. Collaborate with product, engineering, design, marketing, and founders while supporting new app launches and using AI tools to accelerate analysis.

Analyzes courier acquisition funnels across paid, referral, SEO, and organic channels in more than 20 countries. Tracks referral quality and fraud, supports campaign and creative management on Meta, Google Ads, and TikTok, and provides optimization feedback. Uses SQL and Python to query data and automate reports, while building spreadsheets and Looker dashboards to visualize the acquisition funnel from initial engagement through first order.

Designs and maintains financial crime data models, datasets, detection logic, monitoring rules, dashboards, and analytical tools. Owns end-to-end analytics delivery, including requirements gathering, data transformation, validation, deployment, and quality controls. Supports regulatory audits by ensuring data traceability and auditability, and contributes to automation across screening, transaction monitoring, and alert-handling processes.

Lead analytics for subscription products and web funnels, partnering with Product, Marketing, and Data teams to improve conversion, retention, and LTV. Build trusted dashboards, SQL data models, event tracking structures, funnel and cohort analyses, and A/B testing insights. Monitor metrics, identify anomalies, communicate recommendations, and mentor junior and mid-level analysts while maintaining reliable reporting and data foundations.

Use People data to support HR, Talent, Finance, and regional decisions. Build automated dashboards and reports, write and model BigQuery SQL, develop lightweight internal tools, design AI-powered workflows, and maintain data quality across HR systems. The role requires communicating insights to nontechnical stakeholders while protecting sensitive compensation and performance data.

Build and improve Enfuce’s people-data foundation by cleaning, structuring, connecting, and governing data across systems. Develop trusted BI reporting, analyze engagement, retention, workforce efficiency, and headcount trends, and provide actionable recommendations. Define success measures and evaluate people initiatives. Partner with the People, Data & AI, Finance, and People Product teams to support AI-powered automations and products using reliable data.

Analyze demand planning performance, forecast accuracy, demand patterns, and business drivers. Develop dashboards, scorecards, reports, and monitoring solutions; validate data; conduct root cause analysis; support demand and business reviews; and provide actionable recommendations. Partner with planning, commercial, finance, supply planning, technology, and external stakeholders on transformation, process improvement, testing, governance, and adoption initiatives.

Lead predictive audience modeling and advertising measurement for Connected TV. Analyze campaign exposure, reach, frequency, attribution, incrementality, conversion, engagement, retention, and re-engagement. Build scalable visualizations and reporting, establish rigorous measurement methodologies, validate and monitor models, and present commercially relevant insights to clients, partners, and internal stakeholders. Collaborate with Data Engineering, Product, Commercial, and Advertising teams while applying statistical and machine learning expertise to behavioral and advertising datasets.

Analyze FMCG sales, pricing, promotions, customer, product, margin, market share, and competitor data to support revenue growth management. Develop pricing and price elasticity models, identify commercial opportunities, create visualizations and actionable insights, and translate analytical needs into product requirements, user stories, and business rules. Collaborate with stakeholders, product managers, data engineers, developers, and commercial teams to build scalable digital analytics solutions.

Analyze, model, validate, and deliver regulatory and compliance reports across jurisdictions. Build optimized data models, dashboards, and visualizations using modern data-stack tools; manage reporting requirements and automate reporting processes. Collaborate with data, finance, compliance, and regulatory reporting teams to ensure accurate, traceable, and timely submissions to regulators and auditors.

Supports People Analytics by combining data sources, improving data quality, designing KPIs, maintaining Tableau and HR reports, writing SQL, and automating processes with Python and Google Apps Script. The intern reports on employee performance, engagement, leadership, diversity, and inclusion metrics; communicates insights to nontechnical stakeholders; and supports data-informed People Strategy projects while exploring generative AI opportunities.

Analyze and improve fraud signals and user segmentation for Puzzleplay’s rewards platform. Investigate suspicious and manually reviewed users, monitor segment effectiveness, identify gaps in detection, and recommend verification tools. Collaborate with product and data teams to turn analysis into operational fraud controls across different markets as fraud patterns evolve.

Analyze fraud signals and user segments for Puzzleplay’s rewards platform. Investigate suspicious and ambiguous users, refine fraud detection criteria, monitor segment effectiveness, and collaborate with product teams on verification methods and operational fraud controls across markets. Recommend third-party tools and identify signal gaps as fraud patterns evolve.

Processes and maintains global investment data, ensuring accuracy, completeness, coverage, and timely delivery. Collaborates with global data teams, fund companies, and internal clients; manages data acquisition relationships and issue resolution. Develops analytical tools, improves procedures, documents use cases, and translates client requests into specifications and user stories. The role requires fluent English and French, financial industry knowledge, strong organizational skills, and proficiency in Microsoft Excel.

Lead marketing analytics initiatives, including statistical analysis, campaign optimization, LTV modeling, incrementality analysis, data visualization, and third-party data pipeline development. Partner with marketing and cross-functional teams to identify growth opportunities, deliver actionable insights to senior stakeholders, and prototype AI-driven automation for recurring analytics workflows and improved decision-making.

Analyzes media data and translates findings into product logic, insights, and decisions. Develops budget allocation tools using reach curves and scenario modeling, evaluates product outputs, automates tasks with scripting, and partners with data scientists to validate algorithms and improve product features. Supports global product initiatives across regions and clients while applying media analytics expertise.

Analyze campaign and business performance data, develop KPIs and measurement frameworks, produce regular and ad-hoc reports, translate complex datasets into actionable insights, and collaborate with cross-functional teams to improve campaign performance and reporting methodologies.

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.

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.