Top Data Analyst Jobs in Madrid

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.

Analyze production drive-thru voice AI data, build SQL reports and dashboards, monitor KPIs, identify conversation error patterns, and improve NLU models, conversation flows, and LLM behavior through machine learning and rule-based techniques.

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 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 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.

Own GTM and sales analytics across pipeline performance, forecasting, funnel conversion, win/loss analysis, lead and account scoring, territory planning, quota modeling, and capacity planning. Partner with RevOps, Sales, Product, Finance, and Analytics Engineering to improve metric definitions, Salesforce and product data models, dashboards, and decision-making. Translate complex analysis into clear recommendations for GTM leadership.

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.

Analyze large datasets to identify trends and deliver actionable insights; design and monitor KPIs; build and maintain dashboards and reporting frameworks; conduct ad hoc analyses; ensure data quality and support reporting infrastructure in partnership with product and business teams.

Early-career Data Analyst responsible for designing and owning core metrics and dashboards, analyzing transaction/customer/credit data to inform credit, fraud, AML, portfolio and growth decisions, building data pipelines and automations with SQL and Python, partnering with cross-functional teams, and owning compliance reporting. Emphasis on turning ambiguous problems into reliable analytical systems and applying GenAI/LLMs for practical automation.

Partner with Product teams to analyze user journeys, run A/B tests, build dashboards, extract insights using SQL, Tableau and Amplitude, and collaborate with Data Platform engineers to drive data-informed product decisions.

Partner with founders and cross-functional teams to analyze financial and operational data, build executive dashboards, create P&L and margin analyses, forecast and model unit economics, identify cost leaks, reconcile transactions, and present recommendations to improve profitability, cash flow, and business performance.

Partner with Marketing, Sales, Finance, Product and other teams to turn business questions into actionable analysis. Own end-to-end analytics: build datasets and dashboards (dbt, LookML), maintain metric definitions and caveats, use and curate agent tooling for trustworthy answers, and contribute small data platform and pipeline improvements.

Design, build, and maintain Power BI dashboards and Microsoft Fabric data pipelines. Integrate Dynamics 365 data, ensure data quality and governance, deliver executive insights, forecasting, and strategic analysis. Partner with sales, operations, and finance leaders to translate requirements, promote self-service analytics, and document KPIs and reporting logic.

Use SQL and Python to analyse transaction monitoring and fraud rule performance, identify patterns and anomalies, reduce false positives, and prioritise high-risk cases. Partner with FinCrime, Product, Compliance and Data teams to improve controls, data pipelines and detection logic, support scoring and future ML use cases, and translate analysis into actionable recommendations that balance fraud prevention with customer friction.

The Tableau Developer will design, build, and maintain Tableau dashboards, optimizing performance and ensuring data accuracy while collaborating with stakeholders.

As a Senior Data Analyst, you will analyze data, create reports, manage data pipelines, and provide insights to influence product decisions. You will collaborate with various teams and perform A/B testing.