Top Data Analyst Jobs in Fortaleza

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.

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

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

Owner of Growth experimentation and acquisition-to-conversion analytics: design rigorous tests (power, sample size, anytime-valid monitoring), produce readouts, and build a Python/dbt/Lightdash self-serve experimentation layer. Maintain a trusted funnel model (visitor→lead→customer) across channels, reduce reruns via instrumentation checks, and partner with CRO, Growth PMs, and performance marketing to turn analysis into measurable conversion wins.

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.

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.

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.

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.

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.

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.

Build and own a forecasting model for clinical site payments outside Medidata Payments, link forecasts with Medidata, produce client-ready deliverables, ensure revenue recognition compliance, support audits, reconciliation at study closeout, and collaborate with FP&A, Clinical Payments, Project Analysts, and other stakeholders.

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

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.

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.

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.

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.

Manage data migrations and reporting for new hotel clients: extract, clean, map, validate CSV/Excel data, troubleshoot formatting issues, run post-migration audits, and coach clients on building and automating operational and financial reports to track KPIs.

The role involves developing predictive analytics models using Python, creating reports, conducting data evaluation, and communicating insights to support business decisions.

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.