Top Data Analyst Jobs in Brazil

Develop scalable, secure data pipelines and end-to-end data solutions for consulting clients. Collect, clean, transform, and analyze complex datasets; apply statistical methods; create models, visualizations, reports, and dashboards; and provide actionable recommendations. The role also involves troubleshooting system issues, supporting releases and downtimes, maintaining data quality and controls, collaborating with stakeholders, and mentoring junior developers. Remote work includes occasional infrequent travel to the United States.

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.

Develop and maintain SQL-based reporting, ad hoc analyses, and Power BI dashboards supporting order management, pricing, customer services, finance, and digital marketing. Validate data, document reporting logic and business rules, gather stakeholder requirements, identify trends, and translate business needs into actionable insights. The role collaborates with global teams across regions and time zones while applying data governance and reporting best practices.

Own end-to-end analyses, build trusted Snowflake and dbt reporting infrastructure, create Hex dashboards, investigate metric anomalies, ensure data quality, document metrics, partner with stakeholders, use AI responsibly, and mentor analysts.

Analyze data and deliver actionable insights for Retail Media. Build and maintain Power BI dashboards, perform SQL and Python analyses, leverage AI tools to scale reporting, present findings to stakeholders, and document methods and processes to support data-driven decisions.

Partner with stakeholders to analyze large datasets, build and maintain Power BI dashboards and semantic models, perform exploratory analyses and root cause investigations, define KPIs, apply visualization best practices, and translate findings into clear narratives for technical and business audiences while leveraging SQL, DAX, and AI tools.

Design and maintain dashboards and reports, perform deep-dive analyses to identify trends and anomalies, ensure data integrity with engineers and data scientists, automate reporting, and translate complex datasets into clear insights for non-technical stakeholders.

Build and maintain enterprise BI dashboards, reporting suites, optimized SQL queries, and analytical models. Analyze cloud data using platforms such as Snowflake, Databricks, and BigQuery, while partnering with stakeholders to define KPIs and deliver actionable insights. Manage analytical work independently within Agile sprints, ensuring data accuracy and effective collaboration across distributed teams.

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.

Collects, models, processes, and analyzes data from multiple sources to support strategic and operational decisions. Develops dashboards, reports, KPIs, and business intelligence solutions; automates recurring processes; ensures data quality, governance, and validation; and translates business requirements into actionable insights. Collaborates with Engineering, Data, Product, and Business teams while documenting solutions and supporting data users.

Design and maintain end-to-end Power BI BI solutions, use SQL to query and prepare data, create interactive dashboards, translate findings into narratives, collaborate with international stakeholders, and deliver ad hoc analyses to solve business problems.

Analyze billing and support performance, build and maintain data pipelines, apply statistical forecasting and A/B testing, collaborate cross-functionally, document analyses, and provide recommendations to reduce financial risk, disputes, churn, and operational inefficiencies.

Collect, prepare, validate, and report statistical data for property and casualty insurance. Develop and maintain reports and analytic tools, support metadata and data dictionary upkeep, and coordinate with actuaries, product managers, regulatory affairs, finance, and IT to meet reporting requirements.

Build scalable analytical solutions and dashboards using Power BI, Databricks, SQL and Python. Design KPI frameworks, perform statistical analysis and experimentation, ensure data quality and governance, partner with Product/Commercial/Tech teams, and communicate insights to stakeholders.

Lead analytics for the curriculum subscription/ecommerce business and Post-Sales, partnering with stakeholders to deliver GTM, retention, and financial insights. Build and maintain data models and pipelines with SQL and dbt, automate and maintain BI dashboards (Sigma, Tableau), own weekly business review source files, and translate analyses into actionable recommendations.

Partner with product, commercial, and engineering teams to design KPIs, analyze large datasets using SQL and Python, build Power BI semantic models and dashboards, run experiments and root-cause analyses, leverage AI tools to accelerate analytics, mentor analysts, and translate findings into actionable business recommendations.

Lead translation of business needs into data requirements, validate and ready data, design data models and semantic layers, build and maintain reports/dashboards, collaborate with IT and business partners, and promote self-service analytics.

Build, maintain, and optimize data pipelines and ETL integrations (BigQuery, Fivetran, dbt). Design automations (n8n/Zapier/Make), ensure data quality and system reliability, document workflows, troubleshoot pipeline issues, and translate business needs into scalable systems to eliminate manual work.

The role involves designing business intelligence solutions in Power BI, utilizing SQL and Python for data analysis, and applying best practices in data visualization.