Top Data Analyst Jobs in Portugal

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.

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.

Lead the identification, mapping, cataloging, and documentation of organizational data assets, relationships, source systems, data flows, business rules, and end-to-end lineage. Collaborate with data owners, stewards, business teams, and architects to establish governance practices, improve data quality, manage metadata, identify information gaps, and support analytical, operational, and AI initiatives. Apply data modeling principles to structure enterprise data architecture.

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.

Supports market data compliance with exchange regulations and licensing requirements. Maintains license and customer inventories, verifies end-user classifications, prepares usage reports, researches regulatory changes, and coordinates compliance inquiries with exchanges, clients, and internal teams. The role also helps define requirements for compliance tools, improve processes, prepare audits, and maintain accurate documentation.

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.

Analyze data using Python and SQL databases while working in Agile environments with CI/CD tools. The role involves collaborating with dynamic technology teams across hybrid and remote projects in Portugal, communicating effectively in English, and participating in a supportive professional development community.

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.

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.

Analyze data to identify patterns and trends, monitor operational data, develop SQL queries, and create reports for business decisions.

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.

Collect, clean, and organize data from multiple sources; build scalable Power BI dashboards; perform basic statistical analysis; reverse-engineer existing data structures and reports; collaborate with cross-functional teams to meet data needs.

Designs, implements and tests data warehouse solutions, performs technical analyses, documents technical designs, supports UAT and quality testing, liaises with business stakeholders, proposes platform improvements, and reports to the Data Hub Chapter.

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.

Collect and translate business requirements into technical BI solutions; build and optimize SQL queries; design Power BI dashboards; ensure data quality with Data Engineers; perform root-cause analyses and present actionable insights to stakeholders throughout BI project lifecycles.

Translate business needs into technical BI requirements, build and optimize SQL queries, create Power BI dashboards, perform root-cause data analysis, ensure data quality with engineers, and present insights and recommendations to stakeholders throughout BI project lifecycles.

The Data and Analytics Analyst will create reporting artifacts, support analytics initiatives, and partner with stakeholders to deliver business insights using various data tools and methodologies.

Support identification, documentation and governance of data assets across domains. Map data entities, document sources, flows and business rules, collaborate with Data Owners/Stewards, identify data quality gaps, maintain documentation, and contribute to data modelling and governance framework improvements.

Design and implement a data governance framework, build automated data quality checks, investigate root causes of data issues, extract and analyze large datasets, and create dashboards and documentation to improve data accuracy and completeness while collaborating with product, engineering, and operations teams.