Top Data Analyst Jobs in Brazil

The Senior Sales Data Analyst will analyze data, generate performance reports, and create insightful dashboards to aid sales leadership and strategic decision-making.

Drive marketing funnel analytics and attribution: define KPIs, build dashboards, run campaign and predictive performance analyses, maintain data integrity across marketing systems and Salesforce, reconcile systems, partner with BI/Finance/GTM teams, and create process and training documentation to inform strategy and forecasting.

The Senior Analyst in Legal Compliance conducts AML investigations, performs data analysis using SQL and Excel, and documents findings to support compliance efforts.

Drive product decisions for Brazil by owning team KPIs, performing analyses, building data assets, sizing impacts (A/B testing), and partnering with PMs, marketers and engineers to prioritise and measure product improvements and launches.

Lead product-focused risk analytics: design and scale risk data infrastructure, build control frameworks and metrics, partner with product, engineering, risk and compliance to reduce financial crime and ensure regulatory controls are effective.

Perform data mining and analysis on large datasets to detect customer compliance and fraud risks. Build and run monitoring processes, review customer regulatory/compliance data, investigate and escalate issues, and recommend mitigation actions. Support customer meetings and collaborate with internal partners to improve processes and maintain payment system integrity.

Collect, clean, and integrate data from multiple sources; build complex analytics solutions and dashboards (Power BI); collaborate with stakeholders and IT to define requirements; ensure data quality and compliance; lead UAT, technical specs, and troubleshooting for insurance-focused data initiatives.

As a Data Analyst II, you will enhance reporting capabilities, develop data tools, collaborate on insights, and maintain data quality at Brex.

The Data Analyst will design interactive dashboards, model data, perform ETL processes, and collaborate with teams to enhance data-driven decisions using Power BI.

Investigate and resolve data discrepancies, analyze incidents, and validate data using SQL. Monitor data trends, review application code for workarounds, document and communicate data quality issues, and collaborate with cross-functional teams to support production operations and change requests.

Support supply chain strategy by building ETL and visualization tools, performing statistical and predictive modeling, conducting ad-hoc analyses, developing KPIs, and partnering cross-functionally to optimize supply chain efficiency, reduce costs, and enable data-driven decisions.

Use data mining, BI tools and automation to extract, validate, and analyze tax-related data from ERP/SAP and other sources. Build dashboards, drive process improvements, support tax compliance and partner with tax, finance, and IT teams on analytics and tax technology projects.

Lead analytics engagements for enterprise clients using observability and digital experience data. Manage 4–8 accounts, deliver dashboards and reports, perform ad-hoc analysis, configure Dynatrace solutions, present findings to technical and executive stakeholders, and influence product roadmap and client performance strategies.

As a Regulatory Data Analyst, you will model data, manage regulatory reporting solutions, build dashboards, and explore AI solutions to enhance regulatory processes.

Develop analytics solutions, collaborate on requirements, manage data quality, and create visualizations while improving reporting and platforms.

Design and maintain Power BI dashboards, build data models and DAX measures, extract/transform data with SQL and Excel, automate reports, perform data quality analysis, and present insights to finance and business stakeholders.

Analyze fraud trends and monitor metrics (fraud losses, false positives). Build dashboards, features, rules, and models to detect and prevent fraud. Perform human-in-the-loop reviews, collaborate with Risk Operations, Payments, Growth, and senior management, and improve operational feedback loops.

Analyze transactional and operational data to detect and reduce fraud, build and maintain fraud rules/features/models, create dashboards and reports, perform human-in-the-loop reviews, and partner with Risk Operations, Payments, Growth, and leadership to improve processes and mitigations.

Analyze fraud patterns and metrics to reduce fraud losses and false positives. Build dashboards, fraud features, rules, and models. Perform human-in-the-loop reviews, improve operational processes, and provide actionable insights to Risk Operations, Payments, Growth, and senior management.

Build and maintain analytics data models, dashboards, and reports. Use SQL (Postgres, Trino, Iceberg) and dbt to power financial metrics. Perform deep-dive analyses using SQL and Python (Jupyter, Pandas) to answer business questions, operationalize data, and improve reporting and automation.

As a Data Analyst, you will analyze complex data sets, build KPIs, generate actionable insights, and collaborate with engineering teams for process improvements.

Analyze customer behavior and product performance using large datasets; build dashboards, reports, and visualizations; develop queries and data models; perform statistical analysis, forecasting, segmentation, and A/B testing; collaborate with cross-functional teams and present actionable insights to stakeholders while improving data quality and analytics processes.

Perform exploratory data analysis, build and maintain Power BI dashboards, ensure data quality through cleansing and validation, collaborate with cross-functional teams to deliver data-driven insights, document methodologies and data assets, and present findings to business stakeholders.

Build and maintain Power BI dashboards and KPIs, perform advanced SQL analyses, monitor data quality, collaborate with product and data engineering, support metric standardization and CI/CD for BI, and deliver ad hoc analyses to inform business decisions.

Design and maintain end-to-end People Analytics solutions in Power BI; use SQL, Python, and Databricks to prepare and analyze workforce data; create executive dashboards and presentations; translate insights into actionable stories; lead analytics technology projects and collaborate with global HR, IT, Data, and product partners to drive adoption and standardization.