Top Data Analyst Jobs in Sao Paulo

Support warehouse operations by analyzing performance data, building dashboards and reports, automating recurring reporting, validating data, and providing actionable recommendations to improve productivity, labor utilization, inventory accuracy, and service performance. Partner with operations leadership for staffing, forecasting, and continuous improvement through statistical analysis and ad hoc investigations.

Deliver actionable insights by designing dashboards, performing ad hoc and deep-dive analyses, tracking KPIs, and partnering with stakeholders and data engineering to support business performance and leadership decision-making.

Perform SQL and Python-based analyses, build dashboards and reporting (Redash/Tableau/Looker/Power BI), partner with cross-functional teams to define metrics, identify opportunities, monitor performance, and use LLMs and automation to scale analytics.

Partner with cross-functional teams to define metrics, write SQL, build dashboards, perform analyses, and deliver actionable insights. Develop Python-based analytics workflows, monitor reports, and use modern AI tools to scale decision-making.

Analyze observability, digital experience, and business analytics data for enterprise clients. Develop reports, dashboards, and recommendations to improve site performance and user engagement. Manage client relationships, present findings to technical and executive audiences, configure Dynatrace solutions, conduct ad hoc analysis, provide training, and represent client needs to product teams. The role combines data analysis, consulting, account management, strategic communication, and digital transformation support.

Provide data analysis and reporting as a virtual assistant: create and maintain reports, perform data entry and validation, generate visual insights, collaborate with stakeholders, track action items, and improve workflows to optimize reporting efficiency.

The Data Analyst will build key data models and metrics for decision-making, partner with stakeholders for analytical insights, create datasets for self-service reporting, and ensure data reliability through quality checks.

The Revenue Operations Data Analyst will analyze datasets, optimize dashboards, and develop data pipelines to support revenue operations and strategic decision-making.

The Chargebacks Analyst will conduct research on credit card chargebacks, minimize losses, review merchant requests, and support merchants in compliance with company policies. They will perform outreach, collaborate with cross-functional teams, and ensure accurate claim processing.

The Senior Associate Decision Scientist role involves providing analytics support by building reports and dashboards, writing SQL, and maintaining data models while collaborating with stakeholders to derive insights.

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.

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.

The Lead Data Analyst will document technical systems, collaborate with engineering teams, manage SME availability, and produce clear, structured documentation.

Work with real-world datasets to clean, transform, and analyze data using Python and spreadsheets; perform exploratory analysis, develop data models, support client reporting, and communicate insights to cross-functional teams to drive e-commerce 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.

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.

Supports commercial performance by analyzing execution tools and commercial data, testing and deploying Salesforce effectiveness capabilities, coordinating cross-functional rollouts, supporting self-service ticket resolution, maintaining the Activity House framework, and promoting tool adoption. The role also contributes to capability development through documentation, tracking, stakeholder communication, and recommendations based on data insights.

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.

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.

Design and maintain Azure-based data pipelines, model and integrate on-prem and cloud data, build Power BI/Tableau dashboards, write complex SQL/Kusto queries, manage cloud costs, and guide teams on data best practices within Agile teams.

Own Finance and Post-Sales analytics and reporting, build board-ready metrics (MRR/ARR, churn, revenue attribution), unify Sales and Post-Sales customer lifecycle, maintain external partner dashboards, and create automated BI dashboards and models in Sigma and Tableau using SQL and dbt, leveraging AI to automate workflows.

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 subscription products: define KPIs, design experiments (A/B testing), analyze lifecycle metrics, implement tracking and data models, ensure data quality, and build dashboards to inform acquisition, engagement, retention, and revenue decisions across cross-functional teams.