Top Data Analyst Jobs in 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 business requirements and data across European analytics platforms, validate data quality, support data mapping and modeling, and develop Power BI dashboards. Translate business needs into technical solutions while collaborating with data engineers and stakeholders across Sales, Underwriting, Finance, and other functions. The role also supports platform improvement, ad hoc analysis, reporting accuracy, and alignment with Hiscox’s data strategy.

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.

Develop and maintain costing reference standards; collect and curate global costing data; define hourly rates and escalation rules; build analytical models to extract trends; ensure compliance with internal storage guidelines; communicate with costing community and contribute structured inputs to the Costing Data Hub and Data Lake for automation and continuous improvement.

Build and maintain R&D KPIs, datasets, metrics, and reporting that support company decisions. Partner with product, engineering, UX, Data Platform, and business teams to define measurable outcomes, improve data quality, document metric definitions, and create reusable data products. Use SQL and systems thinking to trace data from source systems through reporting, recommend actions, and demonstrate business impact across R&D, Customer Success, Sales, Support, and Finance.

Own end-to-end product analytics for the Pro team: build production-grade pipelines and dbt models, define north-star metrics, design A/B tests and causal inference frameworks, create dashboards and metric frameworks, embed AI tooling, and translate insights into product recommendations for leadership.

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.

Design, build, and optimize robust, high-volume data pipelines and data warehouse solutions. Apply Data Vault 2.0 and Kimball methodologies, develop in Python and SQL, use Git, and follow CI/CD best practices to deliver performant data workflows and insights.

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.

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.

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.

Analyze and instrument offsite discovery and SEO/GEO performance for ecommerce sites. Build integrations, ETL pipelines, and models to track organic and AI-driven traffic. Create tooling and frameworks for technical site audits, landing page modelling, SEO experiments, and enablement for product and customer teams.

Analyze large datasets, extract and manipulate data using SQL, and create visualizations using Tableau and Power BI to support business decisions.

Build and maintain Looker/BigQuery dashboards, perform deep-dive analyses on CX and operations metrics (NPS, contact rates, agent performance), quantify business cases for improvements, develop automations and tools, ensure data governance with Data Engineering, and present actionable insights to non-technical stakeholders.

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

Analyze mobile games data to track performance, design and execute A/B tests, report on user engagement, and recommend optimizations.

Transform data from internal databases, external APIs, and surveys into insights. Analyze trends, build dashboards/reports, ensure data quality, partner with stakeholders, and mentor colleagues to support business decisions.

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.

Translate business requirements into data models and technical specs, design and maintain star/snowflake schemas, build and optimize ETL/ELT pipelines (Stambia or equivalent), implement data quality automation, and develop Power BI reports (DAX/Power Query). Act as liaison between business stakeholders and data engineers to ensure data governance and reliable reporting.

The GCP/Power BI Data Analyst will manage incidents, develop data components, optimize data with GCP and Power BI, and collaborate with business units.

Gather, clean, and maintain data from databases, spreadsheets and APIs. Analyze large datasets with statistical methods to find trends and correlations. Build reports and dashboards (Power BI/Tableau/Excel), monitor KPIs, and present actionable insights to stakeholders. Collaborate with cross-functional teams and data engineers to improve data processes and drive business decisions. Must be French speaker (C1) and submit CV in English.