Top Data Analyst Jobs in Lisbon

Designs and maintains scalable ETL/ELT pipelines and batch or real-time data processing solutions using SQL, Python, and Spark. Ensures data quality, availability, and reliability through testing, monitoring, observability, and automated deployments. Supports platform upgrades, migrations, and production operations while collaborating with data and business teams. Contributes to technical reviews, documentation, architecture discussions, and engineering best practices.

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.

Analyzes data to support business and operational needs, develops and maintains data queries, supports reporting and visualization, and works with data processing and integration solutions. Collaborates with stakeholders to deliver data-driven insights using Python, SQL, Power BI, ETL concepts, and tabular technologies.

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.

Designs and maintains data solutions supporting front-office activities. Builds ETL pipelines, data warehouses, dashboards, reports, and analytical tools using Python, SQL, Tableau, Power BI, and related technologies. Collaborates with business stakeholders, sales teams, and traders to deliver actionable insights. Ensures data quality, consistency, and accessibility while contributing to evolving analytics platforms and AI-powered 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.

Design and build robust, performant data pipelines capable of handling large data volumes. Apply Data Vault 2.0 and Kimball data warehouse concepts, develop using Python and SQL, manage code with Git, and understand CI/CD principles. The role is hybrid, with 50% onsite work in Parque das Nações, Lisbon.

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.

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.

Maintain and administer Workday and other HRIS platforms, ensuring data integrity and process quality. Build and maintain complex Workday reports, deliver metrics and analytical insights, investigate data discrepancies, support system upgrades and implementations, and perform functional testing. Translate business requirements into solutions, manage data updates and integrations, coordinate with stakeholders, provide training, and respond to reporting and system-related inquiries.

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.

Owns finance reporting digitalization, master data maintenance, monthly program and function reporting, and divisional consolidation. The role extracts, validates, compiles, and delivers financial data, manages mappings and access rights, coordinates reporting calendars and stakeholders, and serves as a focal point for reporting improvements and new tools. It partners with controllers, accounting, consolidation, and financial systems teams while supporting automation through coding, AI, and analytics platforms.

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.

Lead marketing analytics and M&A data integration initiatives. Harmonize KPIs, attribution, reporting, and data landscapes; build scalable marketing data models and ELT pipelines; create dashboards; analyze advertising and mobile measurement platforms; deliver executive insights; and lead cross-functional analytics projects involving multiple business units.

Deliver and maintain HR reports and dashboards, ensure data quality, develop visualizations, support HRBPs, train users on self-service reporting, migrate SAP BI reports to Workday, enforce GDPR data protection, and liaise daily with central Airbus stakeholders.

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.

Lead end-to-end dashboard projects for cybersecurity risk management: gather requirements, ETL and model data, build and maintain Power BI/Tableau/Dataiku dashboards, apply statistical and basic ML techniques, present insights to stakeholders, monitor data quality, and collaborate across teams to improve reporting.

Analyze commercial and analytical data, gather business requirements, design data models, develop dashboards and reports, and support Data Warehouse/Datahub enhancements to inform business decisions.