Top Data Analyst Jobs in Lisbon

Collect, clean, analyze, and interpret data; build and maintain Airflow data pipelines; optimize code and queries; generate insights and visualizations; liaise with users to assess requirements and business impact.

Defines and maintains data mapping rules, translates business requirements into technical specifications, performs complex data analysis, assesses data availability across source systems, and collaborates with business and IT teams. Documents findings and communicates results effectively while gathering user requirements and interpreting complex data ecosystems and models.

Build and optimize Power BI data models, dashboards, and reports across cloud and on-premises environments. Integrate multiple data sources, improve query and model performance, test solutions, and collaborate with business stakeholders to translate analytical needs into technical solutions. The role operates in an international, cross-functional team and includes occasional on-call support.

Owns fraud risk performance across payment flows by configuring and optimizing fraud models, rules, thresholds, and decision logic. Analyzes fraud KPIs, conducts root-cause investigations, implements risk controls, and translates risk strategy into mitigation actions. Collaborates with Machine Learning, Product, Compliance, and Operations teams to improve fraud detection precision, manage financial exposure, and meet regulatory expectations.

Investigate emerging fraud patterns and modus operandi across merchants by analyzing large-scale transactional data with SQL, R, and Python. Collaborate with Data Science, Product, Engineering, Risk Operations, and Account Management to develop and improve fraud-detection tools. Monitor detection performance, identify gaps and drift, translate findings into actionable insights, and document methodologies. The role supports fraud prevention, detection accuracy, and merchant performance.

Analyze marketing channels, KPIs, attribution, and experiments to improve advertising efficiency and marketing investment decisions. Build dashboards, ETL pipelines, monitoring and alerting systems, and payback prediction models. Generate insights and hypotheses across acquisition, product feeds, creatives, channel mix, and targeting while applying statistical methods and solving complex problems with incomplete data.

Own analytics for Nuitee’s global travel marketplace, analyzing enterprise partners, self-service API adoption, bookings, product performance, and customer behavior. Build and validate dbt models, data pipelines, experimentation capabilities, and analytical products end to end. Partner with senior Product, Engineering, and commercial leaders to establish trusted metrics, resolve reporting inconsistencies, identify growth opportunities, and influence product and business decisions in a fast-moving startup environment.

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.

Analyze and interpret procurement and supply chain datasets, clean and prepare data, build dashboards and reports, and develop automation and digitalization solutions using Skywise and related tools. The role supports KPI standardization, process optimization, data quality, and stakeholder decision-making. It also involves Generative AI applications, collaboration with procurement teams, data governance, and sharing analytics best practices across the organization.

Analyze payments data, integrate complex data sources, maintain performance reports, monitor KPIs, and identify opportunities to optimize payment routing and reduce failures and costs. The role collaborates with Payment Operations, Product, Finance, Customer Support, analysts, and engineers to ensure data quality and deliver actionable insights through ad hoc analysis, dashboards, and automated reporting.

Supports the Data RUN team by maintaining data systems, resolving incidents, developing data components, and implementing system improvements. Uses Google Cloud Platform, BigQuery, Composer, Power BI, SSIS, Python, and SQL for data management, integration, reporting, and analysis. Collaborates with business stakeholders to translate requirements into technical solutions and works within Agile delivery practices. French proficiency at B2 level or higher is mandatory.

Partner with stakeholders, product, and technology teams to solve complex business problems through data. Develop analytical methodologies, uncover business patterns, improve operational efficiency, and deliver strategic recommendations. Build scalable processes, visualizations, and compelling data-driven narratives for senior executives. Contribute to analytics roadmaps and help the organization become more data-driven.

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.

Own regulatory analytics and reporting by building audit-ready datasets, pipelines, dashboards, compliance metrics, and automated workflows. Analyze complex data, monitor quality, support audits and regulatory exams, and deliver actionable insights to compliance teams and leadership. Translate regulatory requirements into accurate reports using Python, SQL, dbt, and Airflow while partnering cross-functionally to manage data issues and remediation.

Analyzes complex and raw data from multiple sources, identifies trends and patterns, evaluates business needs, and develops analytical tools, pipelines, algorithms, and prototypes. The role prepares data for predictive and prescriptive modeling, improves data quality, supports data architects, and collaborates with data scientists to deliver actionable insights.

Analyzes large-scale IoT and real-time data to uncover customer insights, develop visualization interfaces, and create actionable solutions. The role collaborates with customers, engineers, and product teams; delivers technical presentations; designs analytics architectures; optimizes big data systems; and applies statistical analysis, SQL, Python, and visualization tools to support integrated customer solutions.

Work with enterprise customers to analyze live ecommerce data, research fraud trends, build end-to-end technical solutions, and deliver actionable insights using R, SQL, and Python. Collaborate cross-functionally and present findings to technical and non-technical stakeholders.

Analyze payment data to explain performance changes, identify trends and anomalies, and support Product, Risk, Finance, and Sales decisions. Prepare and validate datasets, apply statistical methods, build Superset dashboards and Druid cubes, deliver regulatory and stakeholder reporting, and automate recurring analysis. The role also requires presenting actionable insights, translating business questions into analytical work, and collaborating across departments.

Analyze revenue and profit trends across e-commerce markets, build automated anomaly detection and early-warning systems, conduct root-cause and causal inference analyses, evaluate pricing and category initiatives, and quantify revenue drivers. The role uses SQL, Python, statistics, econometrics, forecasting, regression, and segmentation to produce actionable insights. Responsibilities also include data storytelling, cross-functional collaboration, leadership presentations, and developing automated analytical workflows.

Senior Data Analyst responsible for gathering business requirements, analyzing trends and metrics, creating scalable dashboards, supporting forecasting and A/B testing, and delivering data-driven insights. The role partners with product, business, and data engineering teams to build reliable data sources, identify growth opportunities, and improve customer, sales, and profitability outcomes.

Analyze advertising channel performance, marketing KPIs, attribution, and ROI; build dashboards, ETL pipelines, alerts, and prediction models; monitor statistical anomalies; design data studies and experiments; and generate insights to improve acquisition, product feeds, creatives, channel allocation, and marketing investment decisions.

As a Data Analyst at Air Apps, you'll analyze data to derive insights, create dashboards, and improve product performance while collaborating with teams.

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.

As a Product Analyst at GoCardless, you'll provide data insights to influence product direction and drive change. Collaborating with various teams, you'll analyze data sets, build user models, and enhance payment intelligence products, ensuring data-driven decision-making and scalability in analytics practices.