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 large datasets to identify trends and improve user engagement, customer experience and sales. Build dashboards and datasets to support product decisions, track software usage, collaborate with product managers and engineers globally, and improve data architecture and event tracking for frontend and backend.

Collect, clean, and analyze large datasets; build reports and dashboards; monitor KPIs; automate data workflows using Alteryx; provide actionable insights and stakeholder support to improve operations and decision-making.

Design, build, and maintain data pipelines, ETL, and warehousing for Global Markets front office. Develop dashboards and analytical tools (Tableau/Power BI), ensure data quality, collaborate with traders and sales, and evolve analytics tech including Python, SQL, APIs and AI chatbot solutions.

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

Design and implement data governance and quality monitoring processes. Develop automated checks, analyze large datasets with SQL/Python, create dashboards and reports, identify root causes of data issues, collaborate with product/engineering/operations, and maintain process and data documentation.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Partner with Product and Engineering to define metrics, run root-cause analyses and experiments, build tracking, reporting, and automated alerts, model data in dbt/BigQuery, scale AI-assisted analytics for self-serve, and communicate insights to drive product and business decisions.

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.

Analyze and improve multilingual classifiers, partner with linguistics and engineering teams, validate taxonomy translations, and document findings.