Top Data Analyst Jobs in Barcelona

Lead marketing analytics projects: design and deliver UA performance measurement, LTV/ROAS analysis, experiment design, and attribution frameworks. Partner with UA/marketing to optimize budgets, maintain data quality, create dashboards, and present insights to senior stakeholders. Drive team best practices and tooling improvements.

As a Principal Data Analyst at Zynga, you will shape game strategies, analyze player behavior, design experiments, mentor analysts, and promote data-informed decision-making to enhance player engagement and business growth.

Lead acquisition-focused measurement and Media Mix Modeling efforts. Design, run, and analyze experiments; build scalable analytics, dashboards, and measurement frameworks; advise marketing stakeholders and senior leadership to drive data-driven acquisition strategy.

The Senior Data Analyst will lead analytics solutions, develop statistical frameworks, build data pipelines, and collaborate with marketing teams to improve performance and efficiency.

Analyze and optimize user journeys, conduct funnel analysis, define customer metrics, design A/B tests, and communicate insights to stakeholders.

Partner with the CEO to ideate, validate, and launch mobile apps using a data-first approach. Define KPIs, build dashboards, analyze user behavior and A/B tests, drive product experiments for activation, retention, monetization, and collaborate with engineering, design, and marketing to ship and iterate quickly.

As a Data Analyst at Joko, you will analyze data for trends, build predictive models, create dashboards, and support stakeholders in decision-making.

Own and improve end-to-end reporting pipelines, ensure data quality and scalable automated reporting, partner with stakeholders and engineering to translate business needs into dashboards and analyses, and explore AI-enabled automation for insights generation.

Job posting contains company diversity, inclusion, and anti-scam statements but provides no role responsibilities, requirements, or tasks for the Associate Data Analyst position.

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.

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.

Lead marketing analytics projects for user acquisition and growth: design experiments, measure ROAS/LTV, build dashboards, ensure data quality, and deliver insights to optimize multi-million dollar marketing budgets.

Develop and implement a data governance framework, build automated data quality checks, analyze large datasets with SQL/Python, create dashboards and reports, investigate root causes of data issues, and collaborate with product, engineering, and operations while maintaining documentation.

As a Data Analyst, you'll maintain and improve BI tools, develop Power BI dashboards, analyze data, and communicate insights to support decision-making.

The Principal Game Data Analyst will shape game strategies through data-driven insights, mentor analysts, and improve analytics standards while collaborating with teams on player behavior and product performance analysis.

The Principal Data Analyst will drive data-driven strategies for games, analyze player behavior and product performance, lead A/B testing, mentor analysts, and improve data culture across the company.

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.

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.

Own marketing analytics: monitor campaign performance, maintain dashboards and pipelines, define and track KPIs (CAC, LTV, ROAS), analyze lifecycle and campaign data, and present insights to marketing leadership to inform strategy.

The Senior Development Engineer/Mathematician/Data Analyst will develop algorithms, create statistical models, and implement biometric methods to enhance diagnostic accuracy and support product approvals.

Analyze product, sales, pricing, customer, and usage data to build reports and dashboards (primarily Power BI). Collect and consolidate data from multiple sources, identify trends, generate insights, and support cross-functional stakeholders. Own end-to-end analytics projects, present findings to management, and improve KPIs like upsell and churn.

Analyze product, sales, pricing, customer, and usage data to build reports and dashboards (primarily Power BI). Consolidate multiple data sources, run SQL queries, create DAX/Power Query models, identify trends, deliver insights to stakeholders, and manage analytics projects end-to-end supporting marketing and business teams.

Lead delivery of end-to-end data and analytics solutions: build dimensional models, develop Power BI dashboards, perform exploratory analysis, design Azure-based data pipelines, capture client requirements, run scenario modelling, test and assure solutions, prepare client communications and lead project teams.

Lead data and analytics projects: design dimensional models, build Power BI dashboards, run exploratory analysis, capture client requirements, develop end-to-end data pipelines on Azure, test and assure solutions, support client decision-making, and contribute to business generation and people development.