Top Data Analyst Jobs in Brazil

Lead compliance analytics for Wise’s Latin America operations, partnering with Compliance and cross-functional teams on regulatory reporting, monitoring, testing, and risk insights. Build advanced SQL reporting outputs, automate recurring reports and compliance workflows, improve data quality and governance, and develop efficient data pipelines using analytics and engineering tools. Influence stakeholders, identify high-impact opportunities, manage competing priorities, and contribute to the team’s strategic roadmap.

Build and maintain customer-facing reports, data models, and product analyses that generate actionable insights. Partner with Product, Development, Design, UX Research, and Data Engineering teams to support data products, analytics-ready schemas, and ad hoc data needs. Apply statistical analysis, data warehousing concepts, and structured problem-solving while communicating findings to technical and non-technical stakeholders. Identify opportunities to use AI tools to automate tasks and improve data workflows.

Lead a multidisciplinary analytics team across chat, conversion, retention, AI, and operations. Develop KPI frameworks, dashboards, funnel and lifecycle analyses, experimentation strategies, and actionable product recommendations. Manage and mentor data professionals, establish the analytics roadmap, investigate ambiguous business problems, and partner with Product, Operations, AI, Growth, and leadership to improve conversion, retention, customer experience, and operational efficiency.

Leads a multidisciplinary analytics team across chat, retention, AI, and operations. Owns KPI frameworks, funnels, retention analysis, dashboards, experimentation, and operational analytics. Partners with Product, Operations, AI, Growth, and leadership to identify business drivers, improve conversion and retention, increase efficiency, and turn ambiguous questions into actionable recommendations. The role combines hands-on analysis with team leadership and stakeholder management.

Designs and optimizes Power BI semantic models, DAX standards, transformation layers, dashboards, and data pipelines. Ensures analytics reliability through data normalization, reconciliation, automated testing, and validation against source systems. Acts as a technical expert for the analytics community, reviews models, evaluates emerging and AI-assisted technologies, establishes best practices, and mentors analysts.

Lead product data analyst responsible for marketplace modeling, advanced SQL analysis, A/B testing, reporting, dashboard trust, and self-service analytics. The role partners with product managers and stakeholders to guide decisions, builds documented dbt datasets, maintains metrics and reports in Lightdash, and supports a data-driven culture. This is an autonomous individual-contributor position focused on the Pro supply side of the marketplace.

Own the growth experimentation program, including test design, power calculations, statistical rigor, monitoring, and readouts across web, SMS, sales, and SEO. Build a trusted acquisition-to-conversion funnel covering CAC, LTV, and conversion rates across channels. Extend automated experimentation tooling using Python, Lightdash, dbt, and AI workflows while partnering with CRO, marketing, and Growth PMs to turn analysis into measurable conversion improvements.

Analyze large-scale data, build client-ready dashboards, design data workflows and analytical queries, and apply statistical techniques such as regression, sentiment, fraud, and time-series analysis. The role supports product development, data quality, customer questions, and complex problem-solving while communicating clear insights to product teams and clients.

Analyze demand planning performance, forecast accuracy, demand patterns, and business drivers. Develop dashboards, scorecards, reports, and monitoring solutions; validate data; conduct root cause analysis; support demand and business reviews; and provide actionable recommendations. Partner with planning, commercial, finance, supply planning, technology, and external stakeholders on transformation, process improvement, testing, governance, and adoption initiatives.

Develops and maintains forecasting models for clinical site payments, integrating Medidata Payments data and supporting financial reporting. Analyzes plan-versus-actual performance, budget variances, and forecast risks; prepares client-ready reports and reconciliations. Partners with Revenue Recognition, Clinical Operations, Project Analysis, and planning teams to support audits, change orders, study closeouts, compliance, and sponsor reporting requirements.

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.

Develop and maintain sales and operations analytics reports, dashboards, and visualizations using SQL, Excel, and BI tools. Monitor data quality, analyze operating metrics, identify trends and improvement opportunities, and communicate actionable findings to leadership. Collaborate with business leaders to support sales activities and data-driven decision-making.

Senior individual contributor responsible for product and marketplace analytics, designing and analyzing A/B and multivariate experiments, building dashboards and automated reports, validating instrumentation, and translating findings into executive-facing recommendations to drive growth and marketplace liquidity.

Analyze user behavior, product performance, experiments, and academic research data to guide product decisions and health outcomes. Responsibilities include building Mixpanel dashboards, validating event tracking, querying Snowflake with SQL, developing Python analyses and automation, maintaining data pipelines, creating BI visualizations, conducting user research, performing statistical testing, preparing research manuscripts, and supporting grant-funded projects.

Partner with Finance teams to translate business requirements into data solutions. Develop SQL analyses, dashboards, automations, pipelines, transformations, and validation routines. Support financial close, reconciliations, controls, and regulatory reporting while improving data quality, governance, and traceability. Investigate inconsistencies, document processes, and collaborate with Finance, Engineering, Product, Data, Risk, and Audit teams to deliver solutions end-to-end.

Supports business users with reporting, dashboards, KPI development, data analysis, discrepancy investigation, and analytical problem-solving. Prepares recurring and ad hoc reports, validates data and reporting outputs, documents metrics and resolutions, coordinates fixes with technical teams, and helps improve or automate reporting workflows. The role also translates business questions into analytical requirements and supports stakeholders using self-service data tools.

Manage and update global master data records, execute workflows and mass updates, validate data quality, perform cleansing and compliance checks, and support process improvement, standardization, automation, root cause analysis, and system testing. The role is a seven-month fixed-term position requiring business or industrial engineering studies, intermediate Excel, English proficiency, strong attention to detail, communication, and time-management skills.

Early-career Data Engineering Analyst supporting AIG’s Data Office through a rotational program. Responsibilities include developing cloud-based data pipelines, collecting and transforming data, building modern software systems, and supporting analytics and data science use cases. The role emphasizes data quality, security, compliance, collaboration, analytical problem-solving, and professional development through mentoring, masterclasses, and on-the-job experiences.

Lead executive discovery, process and value-stream analysis, and requirements definition for data, AI, and GenAI transformations. Facilitate workshops, identify automation opportunities, define data and model requirements, support pilots and UAT, manage stakeholder alignment, and measure business outcomes. Serve as a trusted client advisor, use generative AI to accelerate business analysis, ensure deliverable quality, and coach project team members.

Monitor transactions and customer accounts for suspicious activity, investigate suspected fraud, analyze large datasets with SQL and Python, identify fraud patterns, and develop prevention rules and controls. The role also requires documenting findings, tracking emerging threats, and using Claude or equivalent large language model tools to improve productivity, research, and communication.

Monitor transactions and customer accounts for suspicious activity, investigate suspected fraud, analyze large datasets with SQL and Python, identify fraud patterns, document findings, and develop prevention rules, strategies, and controls. The role also requires staying current on fraud threats and detection technologies while communicating complex issues clearly.

Lead a multidisciplinary analytics team across product, retention, AI, chat, and operations. Own analytics roadmaps, KPI frameworks, dashboards, funnel and cohort analysis, retention strategy, conversational metrics, and operational performance measurement. Translate ambiguous business questions into actionable insights, product recommendations, experiments, and measurable outcomes. Partner with Product, Operations, Growth, AI, Customer Experience, and leadership while developing analytical talent and improving data-driven decision-making.

Perform data quality checks, financial reconciliations, and parallel-run validation for migrated reports and dashboards. Investigate variances with Data Engineering, build Power BI quality dashboards, define acceptance criteria with Finance stakeholders, prepare delivery-gate evidence, and document rules and known issues for client handoff.

Own newsroom analytics supporting editorial, audience, and product decisions. Develop dashboards, automated reporting, measurement frameworks, deep-dive analyses, and A/B tests. Maintain reporting data quality and pipelines in partnership with engineering and product teams. Translate findings for nontechnical stakeholders, strengthen analytical practices, mentor junior analysts, and drive adoption of insights across the organization.

Write SQL queries, build dashboards and recurring reports, support newsroom analyses and A/B testing, troubleshoot data quality issues, and communicate findings to editorial, audience, and product partners. The role also involves maintaining documentation, collaborating with data engineering, and using AI tools to automate analytical workflows.